demonstration results: evaluation and opportunities

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under

grant agreement No 646.531

Demonstration results: Evaluation and opportunities

D3.4

2015 The UPGRID Consortium

Real proven solutions to enable active demand and distributed

generation flexible integration, through a fully controllable

LOW Voltage and medium voltage distribution grid

Demonstration in real user environment:

Iberdrola – Spain

DEMONSTRATION IN REAL USER ENVIRONMENT: IBERDROLA - SPAIN

D.3.4 DEMONSTRATION RESULTS: EVALUATION AND OPPORTUNITIES

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PROGRAMME H2020 – Energy Theme

GRANT AGREEMENT NUMBER 646.531

PROJECT ACRONYM UPGRID

DOCUMENT D3.4

TYPE (DISTRIBUTION LEVEL) ☒ Public

☐ Confidential

☐ Restricted

DUE DELIVERY DATE 30/09/2017

DATE OF DELIVERY 30/09/2017

STATUS AND VERSION v10

NUMBER OF PAGES 201

WP / TASK RELATED WP3 / Task 3.4

WP / TASK RESPONSIBLE IBERDROLA / IBERDROLA

AUTHOR (S) IBERDROLA (Ana González, Raúl Bachiller)

PARTNER(S) CONTRIBUTING IBERDROLA (Marta Elorduy, Ainara Fernández,

Roberto González), GE (Javier Sánchez, Mónica

Pintado, Pablo Sanguino, José Miguel Campanario,

Domingo López), ZIV (Laura Marrón, Sonia

Martínez), TECNALIA (Eduardo García, Sergio Gil,

Joseba Jimeno, José Oyarzabal, Sandra Riaño,

Nerea Ruiz, Izaskun Mendia), EVE (Iñaki Bóveda)

OFFICIAL REVIEWER/S EDP Distribuição (Gonçalo Faria), IEN (Aleksander

Babs)

FILE NAME UPGRID_WP3_D3.4_Demonstration results_v10



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DOCUMENT HISTORY

VERS. ISSUE DATE CONTENT AND CHANGES

v00 24/02/2017 Table of Contents (ToC)

v01 14/06/2017 Version of the Introduction and Benefits overview chapters

v02 14/07/2017 Chapter 5 and 7 contributions. Chapters consolidated

v03 09/08/2017 Version with chapters introductions

v04 04/09/2017 Chapter 3 contributions.

v05 06/09/2017 Chapter 4 and Annexes contributions: First draft completed

v06 15/09/2017 Chapter 4 and Annexes: version consolidated

v07 17/09/2017 Version for official review

v08 24/09/2017 Version with consolidated internal WP3 comments

v09 28/09/2017 Version considering Official Reviewers comments

V10 30/09/2017 Final version



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EXECUTIVE SUMMARY

The present deliverable is focused on the performance evaluation of the UPGRID Spanish demonstrator

in different low voltage (LV) domains (e.g. grid operation and maintenance (O&M), new business

processes and Consumer empowerment) conducted over the best part of 2017. The systems and tools

tested were designed, developed and deployed mainly during the first two years of the demonstrator

(2015-2016). This is described in three deliverables (D3.1 [1], D3.2 [2] and D3.3 [3]), which are

summarised as follows, and being the demonstrator streams of work those shown in Figure 1.

FIGURE 1: SPANISH DEMONSTRATOR LINES OF WORK

The UPGRID Spanish demonstrator has been focused on developments aimed at gathering detailed,

enriched and accurate representation of the LV network, covering components, topology, status,

operation, connectivity, performance, loads, etc., in a real time basis. This accurate and reliable LV

network diagram representation is the key to rely O&M decisions on it. This diagram is the foundation of

the Low Voltage Network Management System (LV NMS) deployed in the demonstrator. The latter

system has been deployed in form of two different solutions: the LV NMS Desktop solution for control

centres and the LV NMS Mobile solution (e.g. running in tablets) for LV Field Crews. The LV NMS is not a

standalone system but it has been integrated with others that are already in operation. This has

required the definition of new interfaces with, for example, the Geographic Information System (GIS),

Advanced Metering Infrastructure (AMI) and Supervisory Control And Data Acquisition (SCADA). More

detail can be found in [1].

The development of LV grid remote control operation over smart metering PoweRline Intelligent

Metering Evolution (PRIME) technology is the second key content of the document. Two main

conclusions have been drawn from laboratory tests [1]. Existing PRIME infrastructure can be used, not

only to retrieve metering data from smart meters, but also to support Internet Protocol (IP) traffic which

can serve multiple purposes. One of the main applications is adding remote control operation in LV. In

addition, a standard protocol, such as Simple Network Management Protocol (SNMP), can be used to

retrieve statistics about PRIME networks performance and bandwidth usage which can help grid

Operators to analyse and optimise both metering and remote control traffic.



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FIGURE 2: GENERAL VIEW (NOT ZOOMED) OF PART OF THE DEMONSTRATOR LV NETWORK MODEL

Other additional demonstrator supportive enhancement covered in this deliverable is the analysis of

smart meter events, which is aimed at demonstrating that the existing AMI can be exploited beyond

billing purposes. This work has made possible to develop a methodology and tools to perform a more

rational, automated structuring and offline processing of smart meter events to support maintenance

field work.

The main monitoring, operation and control capabilities developed in the Spanish demonstrator are

depicted in Figure 3 specifically addressed to support LV network O&M (more information in [2]). The

implementation relies on the LV visibility and control enhancements described in [1]. Finally, but not the

least, the demonstrator has also developed a Consumer capacity building web-based tool aimed at

rationally managing energy consumption. This work is summarised in [3].

FIGURE 3: SUMMARY OF DEMONSTRATOR’S MAIN DEPLOYED CAPABILITIES TO FACILITATE AN ADVANCED LV

MONITORING AND OPERATION

All this work exploits four of the most relevant UPGRID Function Objectives [4]: “Monitoring and control

of LV network”, “Smart metering data utilization”, “Network management methodologies for network

Tracing feautures Comprehensive event

management Outage management -

Service restoration Smart meter querying

Planned jobs management

LV infrastructure remote control

(PRIME)

Access and use of historic

information



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operations” and “Novel approaches to asset management”. In fact, [4] has been used as a solid

reference for establishing the demonstrator scope and boundaries. Table 2 (page 29) presents the cross-

match between the demonstrator sub-functionalities and the main lines of work developed in the

demonstrator.

The content of this deliverable showcases the benefits of the Spanish demonstrator which are

highlighted in a qualitative way but also supported by operational field results. Moreover, the main

opportunities identified along the demonstrator were gathered as well as those that are bound to pave

the way for future developments.

The LV NMS, both Desktop and Mobile solutions, have entered in operation in the demonstrator area.

This has allowed to test functionalities in a bigger scale than during the development phase [1][2].

Successful outcomes have been achieved. The Field Crews have benefitted from this solution (see Figure

4) providing them with a real time view of LV network diagram to investigate LV network incidents; a

way to confirm that the supply restoration has been achieved; allowing them to update the network

topology when carrying out LV fuses switching, as well as temporary operations (i.e. cuts and jumpers).

Improvements were identified, based on the field experience, and are already being included in a

system specification (intended to be fully deployed for the entire Iberdrola LV network), that is under

elaboration, and which relies on the UPGRID acquired knowledge.

FIGURE 4: IBERDROLA FIELD CREW USING THE LV NMS MOBILE SOLUTION

PRIME functionalities results, after field testing, also have confirmed the expected results advanced by

the laboratory tests [2]. An architecture that allows multiple applications (i.e. smart meter management

and remote control) on top of a PRIME subnetwork has been designed, developed, validated and

deployed in the field in the scope of the UPGRID Spanish demonstrator project. Regarding this

functionality, the deliverable describes the tests performed, the results of the field deployment (see

Figure 5) and its main benefits, and applicability based on the experience obtained. Additionally,

introducing these services requires a better knowledge and controllability of the PRIME subnetwork. The

field deployment done in the line of obtaining a manageable PRIME subnetwork through SNMP protocol

is also described.

http://www.linguee.com/english-spanish/translation/successful+outcomes.html



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The structured analyses of smart meters events have allowed to identify useful conclusions to be

applied for maintenance purposes (e.g. identify and solve voltage magnitude issues and inventory data

base inconsistencies). Moreover, the opportunity arisen of the new developed software tool that

performs a more detailed smart meter voltage profile analyses is considered quite to be interesting.

FIGURE 5: INSTALLATION OF PRIME GATEWAY DEVICES AT FIELD (LEFT). WEB TOOL FOR MONITORING PRIME

SUBNETWORK (RIGHT)

A special mention must be made about a group of innovative components included in [2]. These

components take the opportunity of evaluating the application of algorithmic and artificial intelligence

techniques to the new set of data that delivered by the smart grids. This can provide new services or

improve those already existing. With this aim, a reference implementation of several components has

been developed with the main objective of checking and comparing their performance as

complementary services or with respect to other grid O&M processes. These components are basically

the Overload forecasting system ([2]), Medium Voltage (MV) State Estimation ([5],[2]), Simultaneity

Factor Estimation ([6] and [2]), Demand Response Simulator ([6] and [2]), Enhanced Outage

Management ([5] and [2]) and Load and Generation Forecasting ([5] and [2]).

The electricity distribution LV grid involved in the Spanish demonstrator covers approximately 2.150

secondary substations (SSs) and 400.000 Consumers. Geographically, it is located in Bilbao and part of

its surroundings (North of Spain). During the demonstrator implementation, the area was extended up

to approximately twice the initial size [4], highlighting the scalability of the network modelling process.

The UPGRID Spanish demonstrator is built on top of the Bidelek Sareak project (http://bidelek.com), a

Bask-Government supported initiative.

http://bidelek.com/



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TABLE OF CONTENTS

EXECUTIVE SUMMARY _________________________________________________________________ 4

TABLE OF CONTENTS __________________________________________________________________ 8

LIST OF FIGURES _____________________________________________________________________ 12

LIST OF TABLES ______________________________________________________________________ 19

LIST OF EQUATIONS __________________________________________________________________ 20

ABBREVIATIONS AND ACRONYMS ______________________________________________________ 21

1. INTRODUCTION ___________________________________________________________________ 24

1.1 DEMONSTRATOR OBJECTIVES ________________________________________________________________ 25

1.2 DEMONSTRATOR CONTRIBUTIONS____________________________________________________________ 27

1.3 DESCRIPTION OF THE DEMONSTRATOR LOCATION ______________________________________________ 32

2. DEMONSTRATOR BENEFITS AND OPPORTUNITIES OVERVIEW: PRESENT AND NEAR FUTURE _____ 36

3. LV GRID OBSERVABILITY AND OPERATION IMPROVEMENT ________________________________ 41

3.1 INTRODUCTION____________________________________________________________________________ 41

3.2 EVALUATION ______________________________________________________________________________ 46

3.2.1 SOUND LV NETWORK DIAGRAM GENERATION ___________________________________________________________ 47

3.2.2 LV DIAGRAM MAINTENANCE __________________________________________________________________________ 53

3.2.3 LV NMS INTEGRATION WITH EXISTING SYSTEMS: INTERFACES _____________________________________________ 57

3.2.4 LV INCIDENT MANAGEMENT: LV O&M __________________________________________________________________ 64

3.3 OPPORTUNITIES ___________________________________________________________________________ 66

3.4 CONCLUSIONS_____________________________________________________________________________ 67

4. USABILITY OF LV SMART METERING PRIME TECHNOLOGY FOR REMOTE CONTROL _____________ 69

4.1 INTRODUCTION____________________________________________________________________________ 69

4.2 MULTISERVICE PRIME SUBNETWORK (LV REMOTE CONTROL OVER LV SMART METERING PRIME

TECHNOLOGY): EVALUATION AND CONCLUSIONS __________________________________________________ 72

4.2.1 LV CONTROL TRAFFIC OVER PLC PRIME - FIELD VALIDATION CONDITIONS ___________________________________ 73

4.2.2 UPGRID CABINET FOR LV REMOTE CONTROL - FIELD DEPLOYMENTS________________________________________ 73

4.2.3 USE CASE 1 : SS WITH EXISTING RTU - RESULTS, PERFORMANCE AND TOOLS _________________________________ 75

4.2.4 USE CASE 2 : SS WITHOUT REMOTE ACCESS - RESULTS, PERFORMANCE AND TOOLS __________________________ 78



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4.2.5 USE CASE 3: LV BACKUP FEEDER SMART-SWITCH APPLICATION - LIMITATION FOUND IN THE DEMONSTRATOR

AREA ____________________________________________________________________________________________________ 80

4.2.6 APPLICABILITY AND NEW OPPORTUNITIES_______________________________________________________________ 82

4.3 MANAGEABLE PRIME SUBNETWORK (SNMP MONITORING): EVALUATION AND CONCLUSIONS _________ 83

4.3.1 REQUIREMENTS FOR A MANAGEABLE PRIME SUBNETWORK ______________________________________________ 83

4.3.2 FIELD VALIDATION CONDITIONS - RESULTS, PERFORMANCE AND TOOLS ____________________________________ 84

4.3.3 TEST RESULTS AND PERFORMANCE_____________________________________________________________________ 88

4.3.4 APPLICABILITY AND NEW OPPORTUNITIES_______________________________________________________________ 88

4.4 CONCLUSIONS ABOUT PRIME BASED FUNCTIONALITIES __________________________________________ 90

5. LV NETWORK OBSERVATION AND MAINTENANCE BASED ON SMART METER EVENT PROCESSING

AND ANALYSIS ______________________________________________________________________ 92

5.1 INTRODUCTION____________________________________________________________________________ 92

5.2 EVALUATION AND CONCLUSION______________________________________________________________ 93

5.2.1 MOST CONVENIENT TYPE OF SMART METER EVENTS FOR ENHANCING LV MAINTENANCE AND OTHER PRACTICAL

PROCEDURE DETAILS ______________________________________________________________________________________ 93

5.2.2 SELECTION OF MAIN ANALYSIS FUNCTIONALITIES ________________________________________________________ 94

5.2.3 DETECTION OF MISSED EVENTS ________________________________________________________________________ 96

5.2.4 FIELD APPLICABILITY OF SMART METER EVENT ANALYSIS OUTCOMES ______________________________________ 97

5.2.5 DETAILED ANALYSIS OF VOLTAGE MAGNITUDES ISSUES AT SUPPLY POINTS: VIRTUAL REGISTER _______________ 99

5.2.6 SUPERVISION METERS MEASUREMENTS TO COMPLEMENT THE EVENT ANALYSIS ___________________________ 102

5.2.7 REFINEMENT OF SUPERVISION METERS INVENTORY: INCONSISTENCIES DETECTION_________________________ 102

5.2.8 CONVENIENCE OF INTERACTIVE RESULT REPRESENTATION _______________________________________________ 104

5.3 OPPORTUNITIES __________________________________________________________________________ 106

6. CONSUMER EMPOWERMENT TOOL __________________________________________________ 107

6.1 INTRODUCTION___________________________________________________________________________ 107

6.2 EVALUATION _____________________________________________________________________________ 107

6.2.1 METERING DATA GATHERING: TECHNICAL SOLUTION____________________________________________________ 107

6.2.2 WEB TOOL FUNCTIONALITIES _________________________________________________________________________ 108

6.2.3 SOCIETAL RESEARCH _________________________________________________________________________________ 118

6.3 CONCLUSIONS AND OPPORTUNITIES _________________________________________________________ 119

7. ADDITIONAL LV OPERATION OPPORTUNITIES: INNOVATIVE SOFTWARE-BASED COMPONENTS __ 121

7.1 IMPROVING OVERLOAD FORECASTING _______________________________________________________ 121

7.1.1 OBJECTIVE__________________________________________________________________________________________ 121

7.1.2 EVALUATION _______________________________________________________________________________________ 122



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7.1.3 CONCLUSIONS AND FUTURE OPPORTUNITIES___________________________________________________________ 122

7.2 IMPROVING MV STATE ESTIMATION _________________________________________________________ 123

7.2.1 OBJECTIVE__________________________________________________________________________________________ 123

7.2.2 EVALUATION _______________________________________________________________________________________ 123


7.3 IMPROVING DSO DECISIONS BASED ON DEMAND SIDE ESTIMATION_______________________________ 124

7.3.1 OBJECTIVE__________________________________________________________________________________________ 124

7.3.2 EVALUATION _______________________________________________________________________________________ 124


7.4 IMPROVING LOAD DISTRIBUTION BASED ON THE SIMULTANEITY FACTOR ESTIMATION _______________ 126

7.4.1 OBJECTIVE__________________________________________________________________________________________ 126

7.4.2 EVALUATION _______________________________________________________________________________________ 126


7.5 ENHANCING THE OUTAGE MANAGEMENT AND THE SUPPORT FOR THE MAINTENANCE CREWS

COMPONENT OBJECTIVE ______________________________________________________________________ 127

7.5.1 OBJECTIVE__________________________________________________________________________________________ 127

7.5.2 EVALUATION _______________________________________________________________________________________ 128


7.6 LOAD AND GENERATION FORECASTING IN SECONDARY SUBSTATION ______________________________ 128

7.6.1 OBJECTIVE__________________________________________________________________________________________ 128

7.6.2 EVALUATION _______________________________________________________________________________________ 129


8. BUSINESS PROCESSES IMPACT ______________________________________________________ 130

8.1 LV OPERATION AND MAINTENANCE__________________________________________________________ 130

8.2 PRIME MULTISERVICE _____________________________________________________________________ 132

8.3 PRIME MANAGEABLE: REAL TIME AMI FAULTS DETECTION_______________________________________ 133

9. CONCLUSIONS ___________________________________________________________________ 134

REFERENCES _______________________________________________________________________ 138

LV NMS MONITORING INFORMATION DISPLAYED_________________________________ 140 ANNEX I.

MULTISERVICE PRIME SUBNETWORK: USE CASE 1 FIELD DEPLOYMENT _______________ 145 ANNEX II.

ANNEX II.1 UPGRID CABINET MODEL 1___________________________________________________________ 145

ANNEX II.2 SIMULTANEOUS AMI AND IP OVER PRIME TRAFFIC_______________________________________ 145

ANNEX II.3 REMOTE CONTROL TRAFFIC OVER PLC PRIME ___________________________________________ 150



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MULTISERVICE PRIME SUBNETWORK: USE CASE 2 FIELD DEPLOYMENT ______________ 156 ANNEX III.

ANNEX III.1 UPGRID CABINET MODEL 2 __________________________________________________________ 156

ANNEX III.2 IP OVER PRIME AS AN ALTERNATIVE TO A SS WITHOUT REMOTE ACCESS ____________________ 156

MANAGEABLE PRIME SUBNETWORK (SNMP MONITORING) FIELD DEPLOYMENT RESULTS162 ANNEX IV.

MANAGEABLE PRIME SUBNETWORK (SNMP MONITORING) DETAILED EXAMPLE – SS ANNEX V.

200000750 ________________________________________________________________________ 181

SMART METER ANALYSIS AND PROCESSING: MACROS TOOLS ______________________ 184 ANNEX VI.

SMART METER ANALYSIS AND PROCESSING: VIRTUAL REGISTER RESULTS____________ 185 ANNEX VII.

ANNEX VII.1 MEASUREMENTS FROM SS_1 (UNDERVOLTAGE) _______________________________________ 185





ANNEX VII.6 MEASUREMENTS FROM SS_6 (OVERVOLTAGE) _________________________________________ 195






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LIST OF FIGURES

FIGURE 1: SPANISH DEMONSTRATOR LINES OF WORK ________________________________________ 4

FIGURE 2: GENERAL VIEW (NOT ZOOMED) OF PART OF THE DEMONSTRATOR LV NETWORK MODEL ___ 5

FIGURE 3: SUMMARY OF DEMONSTRATOR’S MAIN DEPLOYED CAPABILITIES TO FACILITATE AN

ADVANCED LV MONITORING AND OPERATION ______________________________________________ 5

FIGURE 4: IBERDROLA FIELD CREW USING THE LV NMS MOBILE SOLUTION _______________________ 6

FIGURE 5: INSTALLATION OF PRIME GATEWAY DEVICES AT FIELD (LEFT). WEB TOOL FOR MONITORING

PRIME SUBNETWORK (RIGHT) ___________________________________________________________ 7

FIGURE 6: THE FOUR KEYSTONES OF THE SPANISH DEMONSTRATOR ___________________________ 26

FIGURE 7: SPANISH DEMONSTRATOR LINES OF WORK THAT COVER THE SPANISH DEMONSTRATOR

OBJECTIVES _________________________________________________________________________ 27

FIGURE 8: LOCATION OF THE SPANISH DEMONSTRATION: BILBAO (VIZCAYA, BASQUE COUNTRY)_____ 32

FIGURE 9: GEOGRAPHIC AREA COVERED BY THE DISTRIBUTION NETWORK OF THE SPANISH

DEMONSTRATOR (DELIMITED BY THE RED AND BLUE LINES). IN RED, THE AREA DEFINED AT THE

BEGINNING OF THE DEMONSTRATOR – BILBAO (URBAN). IN BLUE, EXTENSION OF THE DEMONSTRATOR

AREA - BARACALDO (SEMI-URBAN) ______________________________________________________ 33

FIGURE 10: THREE DIFFERENT TYPES OF LV SMART METERS DEVICES USED IN THE DEMONSTRATOR __ 34

FIGURE 11: GENERAL VIEW (NOT ZOOMED) OF PART OF THE DEMONSTRATOR AREA (LV NETWORK

MODEL) ____________________________________________________________________________ 41

FIGURE 12: COMPARISON OF NETWORK ELEMENTS BETWEEN THE GIS (LEFT) AND THE LV NMS

NETWORK (RIGHT) ___________________________________________________________________ 42

FIGURE 13: EXAMPLE OF A SS MODEL VISUALISATION IN THE MV SCADA ________________________ 42

FIGURE 14: SIMPLIFIED DIAGRAM SHOWING MAIN INTERFACES BETWEEN SYSTEMS _______________ 43

FIGURE 15: LV NMS SOLUTIONS DEPLOYED IN THE UPGRID SPANISH DEMONSTRATOR: DESKTOP AND

MOBILE ____________________________________________________________________________ 44

FIGURE 16: EXCEL SHEET EXTRACT WHERE LV INCIDENT INFORMATION HAS BEEN RECORDED FOR BEING

ANALYSED FOR EVALUATION PURPOSES __________________________________________________ 47

FIGURE 17: EXAMPLE OF A SS INTERIOR SCHEMATIC SUCCESSFULLY GENERATED. VALIDATION BETWEEN

GIS INFORMATION (ABOVE) AND LV NMS NETWORK MODEL (BELOW) __________________________ 49

FIGURE 18: EXAMPLE OF LINE ASSIGNED TO AN INCORRECT LV SWITCHBOARD. GIS INFORMATION

(ABOVE). LV DIAGRAM GENERATED FROM GIS DATA (BELOW) ________________________________ 50



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FIGURE 19: EXAMPLE OF MISSING LV FEEDER AFTER THE DATA IMPORTING______________________ 51

FIGURE 20: RELATED CUSTOMER CALLS FOR AN OUTAGE ____________________________________ 54

FIGURE 21: OUTAGE HISTORY FOR AUDITING PURPOSES _____________________________________ 54

FIGURE 22: SWITCHING LOG DETAILING THE TEMPORARY OPERATIONS TO RESTORE AN INCIDENT ___ 55

FIGURE 23: THE SAME TEMPORAL ELEMENTS SHOWN IN THE MOBILE SOLUTION _________________ 55

FIGURE 24: FUSE OPERATED ON TABLET. THE FUSE ON THE RIGHT HAS BEEN REMOVED ____________ 56

FIGURE 25: VISUALISATION ON DESKTOP DIAGRAM OF A REMOVED LV FUSE (THE ELEMENT NOT

COLOURED ON THE RIGHT HAND SIDE) AND THE LV CIRCUIT DE-ENERGISED (IN WHITE). A TOOLTIP

DISPLAYS THE FUSE STATUS PER PHASE. __________________________________________________ 56

FIGURE 26: SS MV MEASUREMENT ON THE SCADA__________________________________________ 58

FIGURE 27: SS MV MEASUREMENT ON THE SAME SS OF FIGURE 30 REPRESENTED ON THE LV NMS ___ 59

FIGURE 28: MEASUREMENT REPORT ON SS SUPERVISION METERS EXTRACTED FROM THE MDMS ____ 59

FIGURE 29: SS SUPERVISION METER MEASUREMENTS (ON DEMAND) SHOWN IN THE LV NMS LV

NETWORK DIAGRAM THROUGH THE LV NMS-OMS-AMI INTERFACE ____________________________ 60

FIGURE 30: CONSUMER CALL DISPLAYED ON THE DIAGRAM ALONG WITH INCIDENT NEAR THE FUSE BOX

SYMBOL____________________________________________________________________________ 61

FIGURE 31: CONSUMER SMART METER EVENT DISPLAYED ON THE DIAGRAM AS A PSEUDO CALL NEAR

THE FUSE BOX SYMBOL _______________________________________________________________ 61

FIGURE 32: GEOSPATIAL ANALYSIS TOOL (GSA) REPRESENTATION EXAMPLE. LEGEND: SS = STARS, FUSE

BOXES = CIRCLES WHICH SIZE DEPEND ON THE NUMBER OF SMART METER EVENTS, LV FEEDERS = GREY

SEGMENTS) _________________________________________________________________________ 63

FIGURE 33: GEOSPATIAL ANALYSIS TOOL (GSA) REPRESENTATION EXAMPLE. SS’S ARE CIRCLES WHICH

SIZE DEPEND ON THE NUMBER OF LV NMS INCIDENTS AND GRAPHS WITH INCIDENT CATEGORIES

CLASSIFICATIONS ____________________________________________________________________ 63

FIGURE 34: SS NETWORK ARCHITECTURE WITH AN EXISTING RTU (USE CASE 1). INITIAL SCENARIO (ON

THE LEFT). SCENARIO THAT INCLUDES GTPS TO TEST REMOTE CONTROL TRAFFIC OVER PRIME (ON THE

RIGHT). CCT = DATA CONCENTRATOR, IBD = IBERDROLA _____________________________________ 70

FIGURE 35: PRIME GTPS INSTALLED IN A SS ________________________________________________ 70

FIGURE 36: SCREENSHOT OF THE SNMP WEB TOOL INTERFACE - DATA ACCESS SHOWING NODES

CONNECTED IN THE DEMONSTRATION AREA. NUMBER OF TERMINALS (IN GREEN). NUMBER OF

SWITCHES (IN BLUE) __________________________________________________________________ 71

FIGURE 37: SCREENSHOT OF THE SNMP WEB TOOL INTERFACE – CONFIGURATION MENU __________ 72

FIGURE 38: PORTABLE CABINET TYPE 1 INSTALLED IN FIELD DEPLOYMENT _______________________ 74

FIGURE 39: PORTABLE CABINET TYPE 2 INSTALLED IN FIELD DEPLOYMENT _______________________ 74



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FIGURE 40: BASIC UPGRID ARCHITECTURE OF REMOTE CONTROL OVER PLC PRIME TESTING ________ 75

FIGURE 41: UPGRID INSTALLATION AT TORRE ABANDOIBARRA 2 SS ____________________________ 76

FIGURE 42: IMAGES OF THE REMOTE CONTROL TRAFFIC TEST PERFORMED AT TORRE ABANDOIBARRA 2

SS_________________________________________________________________________________ 76

FIGURE 43: ARCHITECTURE FOR USE CASE 2 SS WITHOUT REMOTE ACCESS DEPLOYMENT (CCT = DATA

CONCENTRATOR, GTP = PRIME GATEWAY, METER = SMART METER) ___________________________ 78

FIGURE 44: USE CASE 2 TEST ENABLING WAN ACCESS FROM THE METER ROOM OF GERNIKAKO

LORATEGIA 3 ________________________________________________________________________ 79

FIGURE 45: LV GRID TOPOLOGY WITH BACKUP FEEDER REQUIRED (FB = FUSE BOX, SS = SECONDARY

SUBSTATION) _______________________________________________________________________ 81

FIGURE 46: LV GRID TOPOLOGY AVAILABLE IN THE DEMONSTRATOR AREA (FB = FUSE BOX, SS =

SECONDARY SUBSTATION) _____________________________________________________________ 81

FIGURE 47: FIELD VISITS TO VALENTIN DE BERRIOTXOA SS WHERE USE CASE 3 DEPLOYMENTS IN THE

FIELD WAS DISCARDED ________________________________________________________________ 81

FIGURE 48: FIELD SS MONITORED SNMP WEB TOOL (CCT = DATA CONCENTRATOR, IBD = IBERDROLA, FW

= FIRMWARE, SS = SECONDARY SUBSTATION)______________________________________________ 84

FIGURE 49: SCREENSHOT OF THE SNMP WEB TOOL PROVISIONING INTERFACE ___________________ 85

FIGURE 50: SCREENSHOT OF THE SNMP WEB TOOL PROVISIONING INTERFACE II __________________ 85

FIGURE 51: SCREENSHOT OF THE SNMP WEB TOOL SCHEDULER INTERFACE ______________________ 86

FIGURE 52: SCREENSHOT SHOWING ADDED TASKS __________________________________________ 86

FIGURE 53: SCREENSHOT OF RECOLLECTED DATA FROM A REAL DATA CONCENTRATOR. NUMBER OF

TERMINALS (IN GREEN). NUMBER OF SWITCHES (IN BLUE) ___________________________________ 87

FIGURE 54: SCREENSHOT OF RECOLLECTED DATA FROM A REAL DATA CONCENTRATOR WITH NOISE

ISSUES. NUMBER OF TERMINALS (IN GREEN). NUMBER OF SWITCHES (IN BLUE) __________________ 87

FIGURE 55: OFFLINE SMART METER EVENT ANALYSIS WITHIN AMI ARCHITECTURE ________________ 92

FIGURE 56: EVENTS ANALYSIS FLOW CHART _______________________________________________ 93

FIGURE 57: FIELD ANALYSIS OF OVERVOLTAGE EVENTS ______________________________________ 98

FIGURE 58: VOLTAGE CURVE ELABORATED BY THE VIRTUAL REGISTER FOR A PARTICULAR SUPPLY POINT

(SMART METER) AND SHOWN THROUGH THE TOOL GUI ____________________________________ 100

FIGURE 59: MEASUREMENTS FROM FB_1 (PART 1)_________________________________________ 101

FIGURE 60: OVERVOLTAGE REPORT RESULTS AT SUPERVISORY METER _________________________ 103

FIGURE 61: EXTRACT OF THE RESULTS OBTAINED AFTER EXECUTING THE VBA MACRO TOOL _______ 103



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FIGURE 62: BAR CHART [NUMBER OF UNDERVOLTAGE EVENTS PER WEEK IN VIZCAYA (2016) ON BASIS

OF ITS DURATION] __________________________________________________________________ 105

FIGURE 63: MAP [NUMBER OF UNDERVOLTAGE EVENTS PER WEEK IN VIZCAYA (2016) ON BASIS OF ITS

DURATION] ________________________________________________________________________ 105

FIGURE 64: TABLE [NUMBER OF UNDERVOLTAGE EVENTS PER WEEK IN VIZCAYA (2016) ON BASIS OF ITS

DURATION] ________________________________________________________________________ 106

FIGURE 65: COMPONENTS ADAPTED FOR THE SPANISH DEMONSTRATOR ______________________ 121

FIGURE 66: MV VOLTAGES (VIA ICCP INTERFACE) __________________________________________ 140

FIGURE 67: MV ENERGISATION STATUS (SS ENERGISED/DE-ENERGISED). IN THIS CASE THE UPPER “FAKE”

SWITCH IS OPENED AND ALL THE LV CIRCUITS DOWNWARDS ARE WITHOUT ENERGY SUPPLY (WHITE

COLOUR) __________________________________________________________________________ 140

FIGURE 68: DISTRIBUTION TRANSFORMER SUPERVISION METER EVENTS ARE DISPLAYED WITH A

FLASHING MARK (İEVENTO!) NEAR THE TRANSFORMER SYMBOL _____________________________ 141

FIGURE 69: CONSUMER SMART METER EVENTS ARE DISPLAYED AS A PSEUDO CONSUMER CALL ON

NEAR THE FB SYMBOL________________________________________________________________ 141

FIGURE 70: DISTRIBUTION TRANSFORMER SUPERVISION METER INSTANTANEOUS VALUES ARE

DISPLAYED NEAR THE TRANSFORMER SYMBOL ____________________________________________ 142

FIGURE 71: PENDING MAINTENANCE WORK INDICATION (“AO” TEXT) _________________________ 142

FIGURE 72: CONSUMER SMART METER INSTANTANEOUS VALUES AFTER AN ON DEMAND

MEASUREMENTS REQUEST ___________________________________________________________ 143

FIGURE 73: SCHEDULED WORK INDICATION (“SCHEDULE” TEXT) ______________________________ 143

FIGURE 74: CONSUMER SUPPLY POINT SYMBOL (FUSE BOX) _________________________________ 144

FIGURE 75: EXAMPLE OF AN INCIDENT REPORT PREPARED BY THE LV NMS REPORTING TOOLS______ 144

FIGURE 76: PORTABLE CABINET TYPE 1 TO BE USED FOR UPGRID TESTING ______________________ 145

FIGURE 77: SCREENSHOT FROM THE AMI DATA CONCENTRATOR BEFORE THE TESTS _____________ 145

FIGURE 78: METERS REGISTERED TO THE UPGRID GTP ACTING AS BASE NODE (MASTER) __________ 147

FIGURE 79: ZIV PRIME MANAGER TOOL USED FOR GTP PRIME PLC DATA ANALYSIS _______________ 147

FIGURE 80: IMAGES OF THE REMOTE CONTROL TRAFFIC TEST PERFORMED AT TORRE ABANDOIBARRA 2

SS________________________________________________________________________________ 150

FIGURE 81: INITIAL SETUP AT TORRE ABANDOIBARRA 2 SS BEFORE THE TESTING _________________ 151

FIGURE 82: REMOTE CONTROL TRAFFIC TEST SETUP AT TORRE ABANDOIBARRA 2 SS _____________ 151

FIGURE 83: FINAL UPGRID FIRMWARE VERSION FOR MULTISERVICE CAPABILITIES OVER GTP _______ 152

FIGURE 84: UPGRID MASTER GTP CONFIGURATION, INTEGRATED INTO THE PORTABLE CABINET ____ 152



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FIGURE 85: REMOTE WEB CAPTURE OF THE SS UNDER TEST _________________________________ 154

FIGURE 86: IBERDROLA SPECTRUM CONFIGURATION CHANGE TO ALLOW LOCAL SCADA ACCESS ____ 154

FIGURE 87: RTU SIMULATED IN A PC OVER WINPCPAW, INSTALLED ALSO AT THE SS UNDER TEST____ 154

FIGURE 88: WIRESHARK CAPTURE OF 104 CONTROL TRAFFIC OVER IP OVER PLC PRIME ___________ 155

FIGURE 89: PORTABLE CABINET TYPE 2 TO BE USED FOR UPGRID TESTING ______________________ 156

FIGURE 90: SCREENSHOT FROM THE AMI DATA CONCENTRATOR BEFORE THE TESTS _____________ 157

FIGURE 91: USE CASE 2 TESTS SETUP AT MIRIBILLA 6 SS REPRESENTING A SS WITHOUT WAN COVERAGE

_________________________________________________________________________________ 157

FIGURE 92: SCREENSHOT FROM THE GTP IN THE METER ROOM (SLAVE) REGISTERED TO THE GTP IN THE

SS (MASTER) _______________________________________________________________________ 158

FIGURE 93: USE CASE 2 TEST PERFORMED AT MIRIBILLA 6 SS_________________________________ 159

FIGURE 94: USE CASE 2 TEST ENABLING WAN ACCESS FROM THE METER ROOM OF GERNIKAKO

LORATEGIA 3 _______________________________________________________________________ 159

FIGURE 95: CONNECTION PROCESS TO THE AMI DATA CONCENTRATOR FROM THE METER ROOM___ 160

FIGURE 96: SCREENSHOT FROM THE AMI OPERATION SYSTEM DURING THE GTP WAN ACCESS _____ 161

FIGURE 97: REAL DATA CONCENTRATOR A: TERMINALS AND SWITCHES ________________________ 163

FIGURE 98: REAL DATA CONCENTRATOR B: TERMINALS AND SWITCHES ________________________ 163

FIGURE 99: REAL DATA CONCENTRATOR C: TERMINALS AND SWITCHES ________________________ 164

FIGURE 100: REAL DATA CONCENTRATOR D: TERMINALS AND SWITCHES _______________________ 164

FIGURE 101: REAL DATA CONCENTRATOR E: TERMINALS AND SWITCHES _______________________ 165

FIGURE 102: REAL DATA CONCENTRATOR F: TERMINALS AND SWITCHES _______________________ 165

FIGURE 103: REAL DATA CONCENTRATOR G: TERMINALS AND SWITCHES _______________________ 166

FIGURE 104: REAL DATA CONCENTRATOR H: TERMINALS AND SWITCHES _______________________ 166

FIGURE 105: REAL DATA CONCENTRATOR J: TERMINALS AND SWITCHES _______________________ 167

FIGURE 106: REAL DATA CONCENTRATOR K: TERMINALS AND SWITCHES _______________________ 168

FIGURE 107: REAL DATA CONCENTRATOR L: TERMINALS AND SWITCHES _______________________ 168

FIGURE 108: REAL DATA CONCENTRATOR M: TERMINALS AND SWITCHES ______________________ 169

FIGURE 109: REAL DATA CONCENTRATOR N: TERMINALS AND SWITCHES _______________________ 169

FIGURE 110: REAL DATA CONCENTRATOR O: TERMINALS AND SWITCHES_______________________ 170

FIGURE 111: REAL DATA CONCENTRATOR P: TERMINALS AND SWITCHES _______________________ 170

FIGURE 112: REAL DATA CONCENTRATOR Q: TERMINALS AND SWITCHES ______________________ 171



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FIGURE 113: REAL DATA CONCENTRATOR R: TERMINALS AND SWITCHES _______________________ 171

FIGURE 114: REAL DATA CONCENTRATOR S: TERMINALS AND SWITCHES _______________________ 172

FIGURE 115: REAL DATA CONCENTRATOR T: TERMINALS AND SWITCHES _______________________ 172

FIGURE 116: REAL DATA CONCENTRATOR U: TERMINALS AND SWITCHES _______________________ 173

FIGURE 117: REAL DATA CONCENTRATOR V: TERMINALS AND SWITCHES _______________________ 173

FIGURE 118: REAL DATA CONCENTRATOR W: TERMINALS AND SWITCHES ______________________ 174

FIGURE 119: REAL DATA CONCENTRATOR X: TERMINALS AND SWITCHES _______________________ 174

FIGURE 120: REAL DATA CONCENTRATOR Y: TERMINALS AND SWITCHES _______________________ 175

FIGURE 121: REAL DATA CONCENTRATOR Z: TERMINALS AND SWITCHES _______________________ 175

FIGURE 122: REAL DATA CONCENTRATOR AA: TERMINALS AND SWITCHES______________________ 176

FIGURE 123: REAL DATA CONCENTRATOR AB: TERMINALS AND SWITCHES ______________________ 176

FIGURE 124: REAL DATA CONCENTRATOR AC: TERMINALS AND SWITCHES ______________________ 177

FIGURE 125: REAL DATA CONCENTRATOR AD: TERMINALS AND SWITCHES______________________ 177

FIGURE 126: REAL DATA CONCENTRATOR AE: TERMINALS AND SWITCHES ______________________ 178

FIGURE 127: REAL DATA CONCENTRATOR AF: TERMINALS AND SWITCHES ______________________ 178

FIGURE 128: REAL DATA CONCENTRATOR AG: TERMINALS AND SWITCHES______________________ 179

FIGURE 129: REAL DATA CONCENTRATOR AH: TERMINALS AND SWITCHES______________________ 179

FIGURE 130: LOCATION FOR THE SS AND THE DATA CONCENTRATOR __________________________ 181

FIGURE 131: THE TWO LV SWITCHBOARD OF THE SELECTED SS _______________________________ 181

FIGURE 132: DATA CONCENTRATOR ____________________________________________________ 182

FIGURE 133: SNMP CONFIGURATION IN DATA CONCENTRATOR ______________________________ 182

FIGURE 134: PROVISIONING OF THE NODE IN THE WEB TOOL ________________________________ 183

FIGURE 135: PROVISIONED NODE ______________________________________________________ 183

FIGURE 136: QUALITY OF PRIME NETWORK DATA STORED IN WEB TOOL AFTER 4 DAYS ___________ 183

FIGURE 137: MAIN SHEET OF ONE OF THE DEVELOPED MACROS. IT CONTAINS THE EXECUTION

CONFIGURATION PARAMETERS (LEFT) AND THE SUMMARY OF RESULTS (RIGHT)_________________ 184

FIGURE 138: EXTRACT OF THE EXCEL TABLE RESULTED FROM EXECUTING THE MACRO THAT ANALYSES

THE TIME OUT OF VOLTAGE LIMITS AT FB LEVEL___________________________________________ 184

FIGURE 139: MEASUREMENTS FROM FB_1 (PART 1)________________________________________ 186


FIGURE 141: MEASUREMENTS FROM FB_2 _______________________________________________ 188



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FIGURE 143: MEASUREMENTS FROM FB _4 (PART 1) _______________________________________ 190








FIGURE 151: MEASUREMENTS FROM FB_10 ______________________________________________ 195

FIGURE 152: MEASUREMENTS FROM FB_11 (PART 1)_______________________________________ 196

FIGURE 153: MEASUREMENTS FROM FB_11 (PART 2) ______________________________________ 197








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LIST OF TABLES

TABLE 1: UPGRID SPANISH DEMONSTRATOR PARTNERS _____________________________________ 24

TABLE 2: HIGH LEVEL CROSS-MATCHING OF THE SPANISH DEMONSTRATOR SUB-FUNCTIONALITIES [4]

AND ITS MAIN LINES OF WORK. IN GREEN, CASES WITH DIRECT MATCH; IN ORANGE, CASES WITH

PARTIAL MATCH) ____________________________________________________________________ 29

TABLE 3: NUMBER OF MAIN LV EQUIPMENT IN THE DEMONSTRATION AREA _____________________ 35

TABLE 4: INTERFACE SUMMARY INVOLVED IN THE LV NMS INTEGRATION _______________________ 43

TABLE 5: CAPABILITIES FOR ADVANCED LV NETWORK MONITORING AND OPERATION FROM THE

OPERATOR PERSPECTIVE PROVIDED BY THE LV NMS DEPLOYED IN THE UPGRID SPANISH

DEMONSTRATOR (MORE DETAIL IN [2])___________________________________________________ 45

TABLE 6: DATA IMPORTING RESULTS AFTER THE FIRST LOAD __________________________________ 49

TABLE 7: DATA IMPORTING RESULTS _____________________________________________________ 50

TABLE 8: SUMMARY OF THE PROCESS IMPROVEMENTS AND BUSINESS BENEFITS IDENTIFIED WITH THE

SOUND LV NETWORK DIAGRAM GENERATION _____________________________________________ 52


LV DIAGRAM MAINTENANCE ___________________________________________________________ 57


LV NMS INTEGRATION WITH EXISTING SYSTEMS____________________________________________ 64


LV INCIDENT MANAGEMENT ___________________________________________________________ 66

TABLE 12: USE CASES FOR FIELD TESTING _________________________________________________ 69

TABLE 13: TYPE OF SMART METER EVENTS FOR LV NETWORK MAINTENANCE ENHANCEMENT _______ 94

TABLE 14: MAIN ANALYSIS TOOL DEVELOPED IN THE DEMONSTRATOR FOR EVENT ANALYSIS ________ 95

TABLE 15: EXAMPLE OF GRAPHICAL PRESENTATION OF RESULTS AFTER EXECUTING THE MACRO TOOL

(LEFT). SUMMARY OF RESULTS OBTAINED AFTER A SUITABLE INCIDENT HAPPENED ON 12/02/2016

THAT AFFECTED 14 SSS (RIGHT). ________________________________________________________ 96

TABLE 16: WORST CASES OF UNDERVOLTAGE EVENTS (AT FB BASE) DETECTED IN THE VIZCAYA AREA _ 97

TABLE 17: WORST CASES OF OVERVOLTAGE EVENTS (AT FB BASE) DETECTED IN THE VIZCAYA AREA __ 98

TABLE 18: SS_1 - METERS FROM WORST FB UNDERVOLTAGE ________________________________ 100

TABLE 19: NUMBER OF SUPERVISION METERS POTENTIAL WRONG LABELLED ___________________ 103



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TABLE 20: SUMMARY OF THE MAIN TEST PERFORMED FOR EVALUATING THE TECHNICAL WEB TOOL

PERFORMANCE _____________________________________________________________________ 109

TABLE 21: PERFORMANCE TEST PASS REPORT_____________________________________________ 111

TABLE 22: LIST OF SS INVOLVED IN THE FIELD TEST OF THE MANAGEABLE PRIME SUBNETWORK ____ 162

TABLE 23: SS_1 - METERS FROM WORST FB UNDERVOLTAGE ________________________________ 185

TABLE 24: SS_2 SMART METERS FROM WORST FB (UNDERVOLTAGE) __________________________ 188

TABLE 25: SS_3 - METERS FROM WORST FB (UNDERVOLTAGE) _______________________________ 189

TABLE 26: SS_4 METERS FROM WORST FB (UNDERVOLTAGE) ________________________________ 191

TABLE 27: SS_5 - METERS FROM WORST FB (UNDERVOLTAGE) _______________________________ 194

TABLE 28: SS_6 SS - METERS FROM WORST FB (OVERVOLTAGE) ______________________________ 195

TABLE 29 SS_7 SS - METERS FROM WORST FB (OVERVOLTAGE) _______________________________ 198

TABLE 30 SS_8 - METERS FROM WORST FB (OVERVOLTAGE) _________________________________ 199

TABLE 31 SS_9- METERS FROM WORST FB (OVERVOLTAGE)__________________________________ 200

LIST OF EQUATIONS

EQUATION 1: SIMULTANEITY FACTOR....................................................................................................... 126



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ABBREVIATIONS AND ACRONYMS

ADMS Advanced Distribution Management System

AMI Advanced Metering Infrastructure

CCT Data Concentrator

CUPS Universal Supply Point Codes

Código Universal de Punto de Suministro (in Spanish)

D Deliverable

DG Distributed Generation

DLMS Distribution Line Message Specification

DMS Distribution Management System

DPF Distribution Power Flow

DSO Distribution System Operator

DTU Distribution Territorial Unit

EV Electric Vehicle

EVE Ente Vasco de la Energía

FB Fuse Box

FTP File Transfer Protocol

FW Firmware

GE General Electric

GIS Geographic Information System

GPRS/3G General Packet Radio Service / Third Generation

GSA Geospatial analysis tool

GTP PRIME Gateway

GUI Graphical User Interface



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HIS Historical Information System

HTTP Hypertext Transfer Protocol

ICMP Internet Control Message Protocol

IEC International Electrotechnical Commission

IP Internet Protocol

IPv4 Internet Protocol version 4

KPI Key Performance Indicator

LV Low Voltage

LV NMS Low Voltage Network Management System

MDMS Meter Data Management System

MIB Management Information Base

MV Medium Voltage

NMS Network Management System

O&M Operation and Maintenance

OFS Overload Forecasting System

OID Object Identification

OMS Outage Management System

PBN PRIME Base Node

PLC Power Line Communication

PRIME PoweRline Intelligent Metering Evolution

QoS Quality of Supply

RTD Research through design

RTU Remote Terminal Unit

SAIDI System Average Interruption Duration Index

SAIFI System Average Interruption Frequency Index

SCADA Supervisory Control And Data Acquisition



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SM Smart Meter

SME Small and Medium Enterprises

SNMP Simple Network Management Protocol

SNR Signal to noise disturbances

SS Secondary substation

SW Software

TDU Territorial Distribution Unit

ToC Table of Contents

VBA Visual Basic for Applications

VLAN Virtual Local Area Network

WAN Wide Area Network

WMS Work Orders Management System

WP Work Package

XML eXtensible Markup Language



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1. INTRODUCTION

The UPGRID Spanish demonstrator started in April 2015. It has been led by Iberdrola Distribución

Eléctrica with the support of GE, ZIV, Tecnalia and EVE, see Table 1. The demonstrator has been

conducted in two main phases. The first one included the design, development, deployment and test

(from a technical point of view) of all demonstrator concepts. The second phase, reported in the present

deliverable, deals with the entrance into operation on the demonstrator solutions and the impacts on

current Distribution System Operator (DSO) processes.

The Spanish demonstrator has been built on top of Bidelek Sareak project taking advantage mainly of

the experience of using an earlier version of the LV NMS, the smart metering infrastructure and the

distribution grid modernization deployed within this project.

TABLE 1: UPGRID SPANISH DEMONSTRATOR PARTNERS

Iberdrola Distribución Eléctrica has been the DSO responsible of the Spanish demonstrator and it has collaborated in all developments and tests. Its distribution network around Bilbao has been used for testing the deployed concepts1.

General Electric (GE) has collaborated on developing and testing the following concepts: sound LV network modelling, LV NMS (desktop and mobile solutions) and interfaces for LV NMS integration.

ZIV has collaborated on developing and testing PLC PRIME functionalities. Moreover, ZIV is one of the equipment providers (e.g. smart meter and supervision solution in SSs) which are installed in the demonstration area.

Tecnalia has collaborated on smart meter event processing and analysis, and facilitated the integration of some innovation components. Tecnalia has also coordinated local Consumer workshops in the demonstration area.

Ente Vasco de la Energía (EVE) has been in charge of developing and testing the Consumer capacity building web-based tool.

The Spanish demonstrator has four deliverables (D), each document associated with one specific task:

Task 3.1_D3.1 – Tools suit for the Advanced Real Time LV network representation [1]

Task 3.2_D3.2 – Tools suite for the smart control and operation of the LV Grid [2] Task 3.3_D3.3 – Consumer Capacity building web-based system [3]

Task 3.4_D3.4 – Demonstration results: Evaluation and opportunities (present document)

The main outputs of Task 3.1, Task 3.2 and Task 3.3 are a set of tools and developments. This implies

that D3.1, D3.2 and D3.3 summarise what has been done in the associated tasks providing means for

evaluating implementations and development results without a live demonstration. To be precise, D3.1

presents mainly the work on gathering a real time basis detailed, enriched and accurate representation

1 In some particular cases it has been extended to other areas as explained in Chapter 5.



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of the LV network; D3.2 describes the main monitoring, operation and control tools developed in the

demonstrator to support these activities in LV, and D3.3 shows the Spanish demonstrator developments

aimed at creating a Consumer capacity building web-based tool. It is worth mentioning that, in order to

overcome the fact that D3.1, D3.2 and D3.3 are confidential deliverables (i .e. not publically accessible),

summaries of concepts (i.e. objectives, contributions, technical basis, etc.) are provided along this

document to facilitate contextual information to understand the demonstrator background and test

results.

D3.4 is organised into seven chapters. The present section, Chapter 1, provides background information

about the demonstrator in terms of objectives, contributions and location. The Spanish demonstrator

benefits and opportunities overview is in Chapter 2. Chapter 3 contains a description of what are the LV

grid operation improvements introduced by the demonstrator. Chapter 4 evaluates the analysis tools

and performance of the deployed remote control over LV smart metering PRIME technology. Chapter 5

presents results regarding the LV network observation and maintenance based on smart meter event

processing and analysis. Moreover, experiences on using the tools from end-users and future

opportunities collected during the demonstrator operation period are distributed in the previous

chapters Chapter 6 reports on the Consumer empowerment tool evaluation. Chapter 7 advances

opportunities derived from innovative software-based components. Chapter 8, supported by contents

of previous chapters, details business processes impacts. Main conclusions reported along the different

chapters are summaries in Chapter 9. Finally, more detailed information (e.g. images, tables, graphs, ...)

about some of the tests conducted are gathered in a series of Annexes at the end on the document.

1.1 DEMONSTRATOR OBJECTIVES

The Spanish demonstrator is driven by four keystones, see Figure 6: data collection from the field, data

transformation into information, application of this information into both O&M and Consumer

empowerment, and last, but not less important, reconsideration of business processes. The

demonstrator has been aimed at assessing these subjects in detail and assembling all of them together

to achieve the expected objectives and impacts.

On one hand, the demonstrator gathers in real or near-real time, a detailed, enriched and accurate

representation of the LV network (e.g. covering components, topology, status, operation, connectivity,

performance, loads and connected generation, etc.). This model is being supported by measurements of

already deployed smart devices in the field (e.g. smart meters and distribution transformer meter

supervision) and those that are being or will be rolled out in a short and medium term (e.g. advanced LV

supervision). The resulted advanced sound LV network representation is the basis, mainly, for the LV

NMS, also developed and deployed in the demonstrator. This overcomes the current DSO lack of both

visibility and detailed knowledge on the LV part of the distribution grid. Moreover, exploring and

optimising the existing electricity and communication infrastructure to allow a rationally evolution of it

is in fact another key aspect of the demonstrator. In this regards, the PLC PRIME functionality extension

for control capability, in addition to metering and billing purposes is one example of that. All the latter

aspects, among others, are paving the way for a MV approach to manage the LV network in terms of



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accurate and near-to-real time visibility, and system integration approach. This is a relevant evolution

that brings new opportunities for the electricity system to deal with short and medium-term challenges

(e.g. Distributed Energy Resources (DER) penetration increase, AMI data tsunami, DSO role as market

enabler...), and for Consumer service improvements (e.g. power supply restoration time improvement,

more accurate and immediate information, ease Consumer participation in the market…).

FIGURE 6: THE FOUR KEYSTONES OF THE SPANISH DEMONSTRATOR

Finally, but not less important, demonstrator developments, once proved efficient, can only be

interiorised and consolidated if current DSOs processes are adjusted in a reasonable manner (without

ruling out the impact that regulation and policy aspects have on them). For this reason, these aspects

should be considered as well.

The Spanish demonstrator objectives are aligned with the previously mentioned premises as follows:

Take advantage of the present smart metering deployment towards the LV grid full sensing and

remote actuation (improving visibility, controllability and operation). Have a sound LV network representation to be the basis for network management tools.

Develop a dispatch tool to support LV network operations: LV NMS. Improvement and extension of the Power Line Communication (PLC) PRIME-based

communications: PRIME multiservice network (remote control operation of LV grid) and PRIME-manageable network (analyse both metering and remote control traffic).

Advanced assistance and support to the grid maintenance crews and grid Operators. Improve the global quality of the LV grid and the services provided to the Consumers. Demonstrate in real user environment improvements in LV networks monitoring and control. Establish a channel to make the Consumer an active, informed and skilled actor in the smart LV

grid.

Field data collection

Data into Information

Info for O&M enhancement and consumer empowerment

Bussiness models



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Identify new DSO processes or how existing ones should be adapted to accommodate UPGRID solutions.

The evaluation of innovative technological approaches ([5][6][7][8]) to some grid O&M processes taking advantage of the new data options the smart grids make possible.

These objectives have been tackled by four work thematic lines (see Figure 7) within the demonstrator

which are summarised next. Specific technical aspects are described in [1][2][3].

LV Network Management System (LV NMS): Developing and implementing new functionalities in a system for advanced distribution network management which earlier first version was tested in

the LV pilot of the Bidelek Sareak project. The system deployed in the Spanish demonstrator is called PowerOn Advantage2. There is a solution for desktop computers (control dispatch) and

other for mobile field crew devices (i.e. tablets). PRIME based functionalities: Developing multiservice PRIME subnetworks (remote control over

IP) and manageable PRIME subnetworks (enhance monitoring capabilities). Smart meter events processing and analysis: Exploring and applying the information derived

from the analysis of existing events generated by smart meters for LV grid maintenance. Consumer empowerment: Improvement of Consumer awareness building a web-based tool.

FIGURE 7: SPANISH DEMONSTRATOR LINES OF WORK THAT COVER THE SPANISH DEMONSTRATOR OBJECTIVES

1.2 DEMONSTRATOR CONTRIBUTIONS

The Spanish demonstrator technical developments are based on the list of UPGRID sub-functionalities

identified in [4] and presented in Table 2. In the UPGRID context, a sub-functionality is defined as an

implementation and/or process (i.e. hardware and/or software) aimed at providing a service to achieve

a purpose facilitated by standards and right technological choices to attain expected impacts. Then,

2 The final LV NMS deployed in demonstrator is based on a newer version of PowerOn product: PowerOn Advantage v6.2.2 (GE) and PowerOn Mobile v6.3.2.SP1 (Yambay), hereinafter called LV NMS Desktop and Mobile solutions respectively. It is an Advanced Distribution Management System (ADMS) solution combining Distribution Management System (DMS) and Outage Management System (OMS) capabilities .



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Table 2 presents a high level cross-matching of the Spanish demonstrator sub-functionalities and its

main lines of work presented in section 1.1. This includes some of the innovative components developed

transversally in the UPGRID project that have been implemented as well [5][6][7][8].

The analysis of Table 2 shows that main contributions are related to “Monitoring and control of LV

network”, “Network management methodologies for network operation” and “Smart metering data

utilisation”. Most of the sub-functionalities are supported by the LV NMS. This is aligned with the key

challenges faced by DSOs nowadays for managing the LV grid:

Ability to collect the correct information in a timely manner.

Ability to process information and motivate decision regarding:

o Network performance

o Consumer service standards

o Future network design options

o Asset management and maintenance regimes

Understanding the dynamic operation of DER connected at LV.

Managing the DER to maintain and secure a compliant network.

Provide a range of services to Consumers that facilitate more cost effective operational options.

For a successful LV management solution, as intended in the Spanish demonstrator, the following

functions and features are required: collect data from multiple sources, share information across

multiple systems (using standard protocols as much as possible), make relevant information available to

the business processes, deliver a continuous process of design, and plan & operate based on a

consistent set of rules and parameters. This leads to a series of expected contributions on different

areas in a short and medium term aimed at addressing the abovementioned challenges. The most

relevant ones are summarised as follows:

Process operation getting efficiency benefits from exploiting the developed sound LV network

digital representation.

New LV network operation and maintenance schemes (e.g. decentralised approaches).

Investigating and solving LV faults having provided up-to-date information to Field Crews (e.g.

mobile solutions).

Adding new capabilities to systems/tools (e.g. LV NMS) derived from the demonstrator

experience.

Broaden the application of PLC PRIME supported on a new LV remote control profile, makes the LV

network more predictable and manageable.

A more rational, automated structuring and processing of the smart meters events improving

distribution grid management processes.

Interface experience using CIM as best practice for future projects.

Get conclusions and criteria about the possible improvement brought by the applicability of

innovative technology to some specific grid O&M processes.



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TABLE 2: HIGH LEVEL CROSS-MATCHING OF THE SPANISH DEMONSTRATOR SUB-FUNCTIONALITIES [4] AND ITS MAIN LINES OF WORK. IN GREEN, CASES WITH DIRECT MATCH; IN

ORANGE, CASES WITH PARTIAL MATCH)

CLUSTER, FUNCTION OBJECTIVES & UPGRID SUB-FUNCTIONALITIES

SPANISH DEMONSTRATOR WORK SCOPE

LV Network Management

System

PRIME based functionalities

Meter Events Analysis and

Processing

Consumer

empowerment

Innovative

components

Cluster 3: Network operations

D7 Monitoring and control of LV networks

D7.1 Operation (control and multiservice) of LV grid devices using PLC-PRIME for

different remote control applications (Concept test)

D7.2 Queries to request advanced meter data to support operation

D7.3 Improvement the LV Network Management System visualisation by integrating data measurements from inside SS (e.g. transformer meter,

advanced LV supervision)

D7.4 Improvement the LV Network Management System visualisation by integrating data measurements from LV network devices (e.g. Consumers SM, EV charging points, DER)

D7.5 Integration of the MV power transformer status from the MV systems to the LV Network Management System

D7.7 Integration of measurement data to support power flow analyses in LV Network Management System



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LV Network

Management System


Meter Events

Analysis and Processing

Consumer empowerment

Innovative components

D9 Network management methodologies for network operation

D9.1 Define a sound LV network (schematic diagrams and parameters of

components)

D9.2 Use CIM for LV network modelling and data exchange between e.g. AMI, GIS, MV SCADA, LV Network Management System

D9.3 Interface to manage PRIME subnetwork with Simple Network Management

Protocol (SNMP)

D9.5 Visualisation of data from LV Management Network System in a geographical context

D9.6 Internal DSO business processes review in relation with Outage Management

D10 Smart metering data utilisation

D10.1 Integration and processing of meter events or/and other sources (e.g. telecom data) in the Outage Management System (OMS)

D10.3 Algorithm to determine connectivity of SM to the grid (identification of phase and line to which each SM is connected to)

Cluster 4: Network planning and asset management



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LV Network

Management System


Meter Events

Analysis and Processing

Consumer empowerment

Innovative components

D11 New Planning approaches for distribution networks

D11.1 Data analytics based on historical network state data to assist network

planning

D12 Novel approaches to asset management

D12.1 Data analytics based on historical network state data to assist maintenance

D12.4

Deploy some mobile devices (e.g. tablet, smart phone) for accessing and

visualise remotely information from LV system (e.g. geographical context, assets and outage location) to support grid crews

Cluster 5: Market design

D13 New approaches for market design

D13.1 Web portal for increasing the Consumer awareness in order to leverage their

participation in electricity markets



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1.3 DESCRIPTION OF THE DEMONSTRATOR LOCATION

The UPGRID Spanish demonstrator is carried out in part of the distribution grid operated by Iberdrola

Distribución Eléctrica, hereinafter Iberdrola, in the province of Vizcaya (in the Basque Country, North of

Spain) as shown in Figure 8. Geographically, it is located in Bilbao (urban area3) and part of its

surroundings (semi-urban area), delimited by the red and blue lines respectively in Figure 9. The LV

electricity distribution grid involved in the Spanish demonstrator covers approximately 2.150 SS and

400.000 Consumers. During the demonstrator implementation, the area was extended (in blue in Figure

9) up to approximately twice the initial size [4]. The main reasons that motivated that extension were

the opportunity of having a more representative sample of data and proving the scalability of

demonstration concepts related to the use of the LV NMS and highlighting the scalability of the network

modelling process.

FIGURE 8: LOCATION OF THE SPANISH DEMONSTRATION: BILBAO4 (VIZCAYA, BASQUE COUNTRY)

3 The zone classification is defined by the regulation (RD 1955/2000) [11]. Urban area: Groups of municipalities of one province with more than 20.000

supply points, including capitals of province, even if they do not reach the latter figure. Semi-urban area: Groups of municipalities of one province with a

number of supply points between 2.000 and 20.000, excluding capitals of province. Rural area: Groups of municipalities of one province with a number of

supply points less than 2.000. Urban network: Semi-urban network.

4 The capital and main city of Vizcaya is Bilbao with 345.122 inhabitants (2014) and 41.60 km².



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FIGURE 9: GEOGRAPHIC AREA COVERED BY THE DISTRIBUTION NETWORK OF THE SPANISH DEMONSTRATOR (DELIMITED

BY THE RED AND BLUE LINES). IN RED, THE AREA DEFINED AT THE BEGINNING OF THE DEMONSTRATOR – BILBAO (URBAN).

IN BLUE, EXTENSION OF THE DEMONSTRATOR AREA - BARACALDO (SEMI-URBAN)

The LV grid involved in the Spanish demonstrator is deployed and managed radially, as the rest of the

Iberdrola LV grid. This happens even when (sometimes) LV network areas that are fed from different SSs

are interconnected through fuse boxes (FBs) in tie points to supply a LV feeder from another SS. The

latter cases might happen when an incident has made the supply restoration impossible from the same

LV feeder or feeder head. Beside this, most of the underground cables are embedded under tube, and

could be easily connected to any others in parallel by just connecting or disconnecting them in manholes

(i.e. cuts and jumper operations). The supply points are connected using a FB which usually feeds, for

example a building with several Consumers downstream. Residential Consumers are normally single

phase fed (phase + neutral or 2 phases) having in most cases, at least, a three-phase meter for building

services (e.g. lifts); while commercial Consumers are typically three phase fed (3 phase + neutral).

The AMI deployment in the demonstrator area to meet the legal mandate for a smart metering in Spain

[16] was mainly completed prior to start the UPGRID project (in some locations even two years before).

This has resulted in 95% of SSs with data concentrators installed to allow smart meters to be effectively

integrated in the AMI system. Only 12% of SSs have 6 Consumers or less connected to and they have not

been equipped yet. These latter cases will have an “ad hoc” solution that will be installed along 2017

and 2018. Taking advantage of the legal AMI deployment, SSs have been adapted with additional

capabilities (i.e. LV measurements, MV supervision and MV automation). This results in having all these

SSs with measure devices at the LV side of distribution transformers and 303 of them with MV

supervision (collecting power measurements, currents and voltages in all MV cabinets except one).



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Additionally, there is MV remote control in 216 SSs (capacity to operate some devices remotely) and

fault pass indicators in some SSs. It is important to note that the latter SSs are also supervised.

As explained, most of the SSs involved in the UPGRID Spanish demonstrator have supervision meters at

the LV side of the distribution transformer providing measurements at the LV switchboard level.

Moreover, there are approximately 495 SSs with Advanced LV supervision that is an Intelligent

Electronic Device (IED), comparable to a smart meter that provides additional measurements (e.g.

voltage, current, powers, etc.) per LV feeder and feeder phase5. This solution also provides connectivity

information to know accurately in which LV feeder each smart meter is connected to6. As a summary,

Figure 10 shows the three different types of smart meters devices that exist in the demonstrator area

according to their location in the LV grid. The collected information, among other, is used to enrich the

sound LV network representation as explained later in the deliverable.

FIGURE 10: THREE DIFFERENT TYPES OF LV SMART METERS DEVICES USED IN THE DEMONSTRATOR

Regarding the field equipment involved in the demonstrator, it is concluded that, apart from the new

generation of devices developed to support IP capabilities over PRIME network (PRIME Gateways

5 At the moment of writing this deliverable, the LV NMS was prepared for receiving measurements on demand provided by these devices but the AMI Head System interface (see Chapter 3) was not programed yet to do that.

6 The connectivity information gathered by 50 of the devices already at field at the beginning of the demonstrator [4] was uploaded (manually) in the LV NMS during the first loading of network data into the LV NMS (technical tests). This allowed preparing the LV NMS for using this detailed information . However, the network extension modelling (Figure 9) entailed uploading the full network data again and the connectivity information provided by the advanced LV supervision was not entered again. Preparing the LV NMS for using detailed connectivity information has been an enhanced that should continue with the necessary automatic uploading process. For test proposes, the connectivity information used has been: GIS information (feeder connectivity) and assigning one third of Consumer per feeder phase. In spite of possible differences, the fact of being able to use more detailed information during incident management is how the demonstrator provides new value.



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(GTPs), see Chapter 4) the rest were either deployed before UPGRID7 or not funded by the project.

Then, most of the information categories sent to the AMI Head System exited before starting the

demonstrator (as stated in key performance indicators (KPIs) 10, 11, 12 and 138 [9]). Therefore, one of

the main contributions of the Spanish demonstrator is to use data already available from field devices

rather than installing new devices. Table 3 shows the number of main LV equipment in the

demonstration area.

TABLE 3: NUMBER OF MAIN LV EQUIPMENT IN THE DEMONSTRATION AREA

Smart meters 370.971

Transformers supervision meters 3.490

Advanced LV supervision meters 495

GTPs 4

7 Only some units might have been installed during the demonstration period but it has been due to the mandate AMI roll out and not within the demonstrator scope.

8 KPI 10: MONITORING INFORMATION CATEGORIES, KPI 11: AVAILABLE INFORMATION CATEGORIES, KPI 12: CHARACTERISED INFORMATION CATEGORIES and KPI 13: AVAILABILITY OF INTELLIGENT NETWORK COMPONENTS.



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2. DEMONSTRATOR BENEFITS AND OPPORTUNITIES

OVERVIEW: PRESENT AND NEAR FUTURE

It is difficult to account each demonstrator for benefits on one individual sub-functionality (Table 2)

since most of them are interrelated. As it has been shown in Figure 6, the Spanish demonstrator is based

on four keystones which serve as a high level thread to showcase the benefits. The following list

provides a qualitative overview of the expected demonstrator benefits (present and near-future) which

are developed, consolidated and evaluated in more detail in the rest of chapters and annexes of this

deliverable. This is much related to the impact on the business process described in Chapter 8.

Increase of AMI infrastructure value: leveraging field data and DSO value increase

The demonstrator contributes boosting the use of existing and new field measurements mainly from

already or planned deployed monitoring LV equipment, for example, smart meters, distribution

transformer supervision meters and advanced LV supervision meters. The legal mandate on smart

metering is opening new opportunities beyond metering and billing. This is aligned with the prevailing

trend, apart from billing purposes, to use the smart meters to monitor and improve the LV grid

[12][13]. The demonstrator has developed integrated solutions (e.g. sound LV network, LV NMS, LV

control over the PRIME infrastructure and processing of smart meters events) based on existing

technologies. This increase in monitoring and controllability of the LV network paving the way to new

opportunities and services to address current and near future electricity distribution challenges and

roles. In this way, the demonstrator is also contributing to facilitate the consolidation and

enhancement of the network as the backbone of the electricity sector and the DSO as market enabler.

This provides additional value to current investments and incentive new ones.

Have a sound LV network representation

The main benefits are:

Provision of accurate and up-to-date information to distribution centre Operator and Field

Crews: accurate knowledge about the LV network.

Availability of new graphical information (e.g. real LV feeders routing, SS interior schematic and

assets attributes).

Detection of information inconsistencies in existing systems (e.g. GIS).

Use of CIM to import automatically data to create/update the sound LV network representation.

The demonstrator has developed a consistent and reliable LV network representation build on top of

work started in the Bidelek Sareak project. It did not exist before. New information and capabilities

have been developed during UPGRID (e.g. automatic data import processes, new pieces of equipment

information added, development of new interfaces and CIM modelling improvement). This model is

complemented with LV and MV field measurements and it is the basis for the LV NMS network

graphical visualization.

http://www.linguee.es/ingles-espanol/traduccion/guiding+thread.html



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Dispatch tool (Desktop and Mobile solution) to support LV network O&M: new monitoring,

controllability and operation capabilities


System integration approach: avoid data redundancy and leveraging existing data.

Implementation of centralised and decentralised solutions for LV network O&M.

Integration of meter events (online) for enhancing Outage Management.

Managing the LV diagram, asset search & query, information and field work management.

The LV NMS is aimed at leveraging the sound LV network representation building new functionalities on

top of that. The interfaces stablished between the LV NMS and other existing systems (e.g. GIS, SCADA,

OMS, AMI, etc.) provide key information to Operators allowing them taking more precise O&M

decisions than before. Some examples are: LV and MV measurements displayed on the LV network

model, being able to request LV measurements (smart meters and supervision meters) on demand,

being aware of LV incidents based on spontaneous smart meters events in addition to Consumer calls,

use smart meter connectivity information for more accurate incident reports and distribution power

flow (DPF), being able to consider planned works and display graphically the impact of MV faults on the

LV network.

Being able to request three phase smart meters measurements on demand from the LV NMS is useful

to narrow down the location of the LV incident (and thus reducing the time required for that) and check

the restoration of the service. Requesting supervision meter measurements support this process as

well.

Moreover the LV NMS provides the benefit of representing network topology changes. This ensures

that any modification (e.g. cuts and jumpers implemented at field during an incident management to

succour one feeder from another) is recorded conveniently by Field Crews in a centralised way. Before,

this kind of information was nowhere with the attendant risk of future field works. In this sense, having

integrated the connectivity information in the system allows the Operator knowing where the

Consumers are connected at any moment. A part from the other advantages pointed out regarding this

feature, it permits keeping updated the connectivity records after performing cuts and jumpers at field.

Then certain Consumers will start appearing connected on the feeder that provides the service to them

from that moment.

Additionally, being able to trace graphically LV circuits based on, for example voltage levels and

energised status up to the corresponding LV feeder head, provides some benefits such as checking in

advance that a cut and jumper at field is compatible regarding voltage level (i.e. if a LV feeder can be

fed by other).

Improve the different factors that impact on global quality of the LV grid: Consumer oriented


Reduce power supply restoration time.



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More accurate and immediate information regarding an incident.

Individual quality of service improvement.

The LV NMS provides the capability to respond more efficiently to LV incidents. Previously there was

almost no information from the LV network. Basically, the only information to realise about the

existence of a LV failure was the Consumer calls. It is worth mentioning that Consumers could be aware

of an electricity supply outage in minutes, days, months or even longer times, depending mainly if they

were or not at home. Now, thanks to the work developed in the demonstrator, the Operator has the

capability of knowing about it before receiving the first call. Then, when Consumers affected by an LV

incident call, they can even receive information about the current situation.

Other type of incidents that can be detected faster without waiting for Consumer calls are the ones

related to a MV fuse blown. This scenario is difficult to detect since there is no trigger in the

corresponding SSs. In these situations the electricity system can still be online by the two unaffected

phases. With UPGRID it is possible to identify one phase fault. The potential impact of this benefit

would not be only on LV Consumers but also on MV indexes such as System Average Interruption

Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI) indexes. Current

regulation starts counting the LV incidents duration from the moment of receiving the first Consumer

call regardless when the incident happens. Then, Consumers have not a value for the early

identification of the incident.

Additionally, thanks to: the connectivity information provided and processing as result of the advanced

LV supervision solution, the sound LV network representation and the LV NMS, more detailed and

accurate LV incident management reports are elaborated now. Before UPGRID, for example, the report

of an LV incident on a single LV feeder phase counted all LV Consumers connected at that LV feeder as

affected (even being the real number of them lower) during a time period equal to the total incident

duration (i.e. since the first call up to the moment the service is totally restored). However, thanks to

UPGRID, it is possible to add into the report more detailed information considering the number of

Consumers who are really affected and the real time each of them have been without service (i.e.

similar approach followed in MV).

A more rational, automated structuring and processing of the smart meter events (offline): assist

maintenance


Detection of potential cases of improvement: voltage deviations.

Detection of repetitive incidents: predictive maintenance.

Detection of data base inconsistencies.

This is another example how the demonstrator exploits data from existing field devices for enhancing

the LV maintenance. In this case, smart meters have been registering events but they have not been

processed yet. Now, the demonstrator has started analysing them in order to explore strategies and

approaches to extract new benefits. In this regards, a selected group of events has been identified

among all existing ones for being considered more interesting for LV maintenance (e.g. undervoltage



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and overvoltage). Thanks to the developed tools and graphical representation of results (graphs and

maps) the maintenance responsible has the opportunity to identify LV network areas that are

registering, a priori, anomalous number of events easily. Moreover, having defined different levels of

data aggregation based on network assets (e.g. SSs, FBs and individual smart meters), the process to

determine the location, cause and then selecting an appropriate solution (e.g. adjust transformer tap

changer positions, change cable type, perform a remote detailed voltage monitoring of selected smart

meters, correct asset data base inconsistences, etc.) is facilitated.

Improvement and extension of the PLC PRIME-based communications: remote control operation of LV

grid and manageable subnetwork

The PRIME manageable subnetwork opens the way to use AMI deployments for further applications

(mainly focused on network operation optimization and remote control capabilities over the LV grid)

and not only for billing purposes. The proposed PRIME network monitoring enhancement (i.e. PRIME

communication channel usage characterization) is a prerequisite to evaluate best approaches to

introduce new applications. Additionally, the regular AMI operation is improved as well since the

performance information included in the SNMP web tool developed for UPGRID project allows

detecting real time issues, for example in AMI data concentrators. This could have also a positive

impact on LV incident management and then on Consumers quality of supply (QoS) since changes in the

PRIME subnetwork status regarding their elements (e.g. smart meters) can be observed.

The LV remote control can start to be assumed within the smart grid functions. MV remote control is

well integrated in the electricity grid operation, although not present in all SSs. Its purpose is to get

information of the grid as well as to operate the grid elements (e.g. switches) remotely and safely.

Remote controllable points in the LV grid will allow the same mode of operation in this LV segment of

the grid.

A practical benefit of this is the reduction of uncertainties regarding LV feeder capacity. As result, the

hosting capacity can be increased. The fact of having more detailed and sound information allows DSOs

to be less conservative regarding the amount of distributed generation (DG) connected into the

network since there would be the certainty that the QoS is not jeopardised. This, together with the

capability of controlling these generation units thought LV grid remote control operation over PRIME

infrastructure, can allow increasing the hosting capacity even more since there is a means, at a

particular moment if required, to reduce the power injected into the network (if approved by

regulation).

Moreover, IP over PRIME implementation can be used by the DSOs as an alternative transmission mean

for SSs where other options are not cost effective. Additionally, remote control for smart-switching is

applicable as well. New LV elements, such as LV smart-switches can be remotely controlled using IP

over PRIME in order to switch to backup lines connected to alternative SSs.

Establish a channel to make the Consumer an active, informed and skilled actor in the smart LV grid

In this way Consumers can discover how they use energy and how they can make savings, using real



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consumption data collected by the smart meters. In short, the aim of the tool is to ensure that users

have enough technically and economically reliable information to allow them to take responsible

decisions to help reduce their electricity consumption. This contributes positively on the active

participation of Consumers and realise the socio-economic benefit that smart grids are envisage to

bring with new opportunities. Dissemination activities are important to make known these kinds of

tools by the end-users.



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3. LV GRID OBSERVABILITY AND OPERATION IMPROVEMENT

The main objective of this chapter is to report on LV grid observability and operation improvement

derived from the work developed in the UPGRID Spanish demonstrator. First, the introduction provides

information to understand main aspects of the LV NMS which are described in more detail in [1][2].

Second, improvements are evaluated based on field experience in the demonstrator and near-future

opportunities are pointed out.

3.1 INTRODUCTION

The LV NMS is an Advanced Distribution Management System (ADMS) solution combining Distribution

Management System (DMS) and Outage Management System (OMS) capabilities. It uses the sound LV

network representation as a graphical basis. This resource provides to the LV NMS a near-real time

detailed, enriched and accurate representation of the LV network (covering components, topology,

status, operation, connectivity, performance, loads and generation connected, etc.). It includes: the

geographic (Figure 11) and schematic (e.g. figure 11, on the right) diagrams, a connectivity model,

measurements and assets information (attributes) to allow the system Operator to visualise, monitor

and control the current state of the LV network through the LV NMS.

FIGURE 11: GENERAL VIEW (NOT ZOOMED) OF PART OF THE DEMONSTRATOR AREA (LV NETWORK MODEL)



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The LV network representation is not a static model. Otherwise it would not represent the state of the

grid on near-real time. The two features that enable this capability are: the use of field measurements

(e.g. smart meter measurements, distribution transformer MV and LV measurements and advanced LV

supervision) and data model import process that ensure Operators be aware of topological changes. The

main data source of this model is the Iberdrola’s GIS. The automatic importation process from the latter

alphanumeric system is an important step forward that determines the quality of the achieved network

representation (i.e. electrical and topological referential integrity). The use of the reference Common

Information Model (CIM) supports this process, for example, facilitating the modelling of new network

elements (non-existing previously in the Iberdrola’s GIS) that have been added to the model (e.g. SS

internal elements and geometry creation for LV cables (routing)) as shown in Figure 12.

FIGURE 12: COMPARISON OF NETWORK ELEMENTS BETWEEN THE GIS (LEFT) AND THE LV NMS NETWORK (RIGHT)

It is important to understand the reasons why having the LV network representation together with the

monitoring enhancements are key resources. For that, it is necessary to explain that distribution

network Operators using MV SCADA do not visualise what is happening beyond the MV side of the

distribution power transformers. There is not such graphical model for LV in the latter system as it can

be observed in Figure 13. Figure 13 (left) shows the graphical representation of a SS in the MV SCADA

where the yellow cross represents the MV side of the distribution transformer. Beyond that, there is not

LV information to be provided to the Operator. Thanks to the UPGRID demonstrator there is now a

comprehensive, accurate and reliable LV network model that, together with the functionalities

developed on top of it (LV NMS), allows relying O&M decisions on it.

FIGURE 13: EXAMPLE OF A SS MODEL VISUALISATION IN THE MV SCADA



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It is worth noting that the LV NMS deployment has not been conceived as a standalone system but fully

integrated with Iberdrola’s third party systems. This integration has been made through a series of

existing and new interfaces with, for example: GIS, AMI, OMS, SCADA and CIS. Figure 14 shows a

schematic representation of the interfaces involved in the LV NMS integration.

FIGURE 14: SIMPLIFIED DIAGRAM SHOWING MAIN INTERFACES BETWEEN SYSTEMS

Table 4 provides a summary of the interfaces involved in the system architecture shown in Figure 14.

TABLE 4: INTERFACE SUMMARY INVOLVED IN THE LV NMS INTEGRATION

Interface Main information involved

GIS to Model Integration Platform Alphanumeric LV network information. Geographic model

update. Data conversion and correction to ensure integrity.

Model Integration Platform to LV NMS LV model update file exchange (CIM).

SIC to LV NMS Consumer information (smart meter id, connectivity, power

contracted and type of Consumer).

OMS to LV NMS

- LV Consumer incident calls (to initialise an incident record).

- MV energisation status (to visualise the impact of MV incident in

the LV network).

LV NMS to OMS Order completion (detailed incident completion report).

LV NMS to AMI (via OMS)

- Meter measurements on demand requests (polling): smart

meters, SS supervision meters, advanced LV supervision meters9

- Historic smart meter measurements on demand request.

AMI to LV NMS (via OMS) Spontaneous smart meter events (to initialise an incident record).

9 As soon as the AMI Head End is prepared to perform on demand measureme nts to these devices that are being installed.



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Interface Main information involved

Outage Planning System to LV NMS Planned LV supply outages (visualisation of the work order in the

LV diagram).

SCADA to LV NMS Voltage measurement at the MV side of the distribution

transformers.

WMS to LV NMS Planned maintenance (to be aware of all maintenance pending

work planned).

The LV NMS deployed in UPGRID project is based on a newer version of the PowerOn product, PowerOn

Advantage v6.2.2. and PowerOn Mobile v6.3.2.SP1 (hereinafter called LV NMS Desktop and Mobile

solutions respectively). Figure 15 shows a simplified architecture scheme of the LV NMS solutions

deployed in the UPGRID Spanish demonstrator.

FIGURE 15: LV NMS SOLUTIONS DEPLOYED IN THE UPGRID SPANISH DEMONSTRATOR: DESKTOP AND MOBILE

Table 5 describes the main capabilities for advanced LV network monitoring and operation provided by

the LV NMS deployed in the UPGRID Spanish demonstrator. Annex I contains a set of figures showing

examples of how the LV NMS user is provided with real or near real time data reflected on the LV

network diagram thanks to the interfaces indicated in Table 4. The LV NMS Graphical User Interface

(GUI) has been defined and designed based on the system Operator’s criteria, requirements and roles

(e.g. colour coding). This also includes the availability of geospatial reporting and analytics tools.

Moreover, these screenshots represent most of the capabilities (Desktop and Mobile solution) listed on

Figure 15.



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TABLE 5: CAPABILITIES FOR ADVANCED LV NETWORK MONITORING AND OPERATION FROM THE OPERATOR PERSPECTIVE

PROVIDED BY THE LV NMS DEPLOYED IN THE UPGRID SPANISH DEMONSTRATOR (MORE DETAIL IN [2])

Capability name Desktop / Mobile

Mobilisation of LV network diagram: Mobilisation of Iberdrola LV network diagram including

map background. Changes to the model including switching and connectivity model updates

available to Desktop and Mobile users in real time.

Desktop and Mobile

Access to asset information: Operational asset model, allowing crews to access up-to-date

asset data from the LV network diagram. Desktop and Mobile

Asset search: Ability to search for assets based on the LV network diagram. Search engine can

use key words such as asset alias or name. Desktop and Mobile

Asset model update: Updates to the LV NMS asset model are available to LV Field Engineers in

real time providing the Mobile device has an active network connection. Desktop and Mobile

Access to Consumer connectivity: Access to Consumer information from the LV network

diagram (supply point identification, address, connected phases, etc.). Desktop and Mobile

Access to meter data: Access to smart meter and supervision data from the LV network

diagram. Desktop and Mobile

Offline usage of LV NMS Mobile solution: Being offline, LV Field Engineers are able to: access

the latest network diagram downloaded by their device when it was last online, search for

assets, and access the last available information of any given asset.

The connection state of the LV NMS Mobile device, including whether the system is displaying

real time or offl ine data, is clearly visible to the field user.

Mobile

Tracing capability: It allows Operators to run pre-configured and ad-hoc traces to quickly

understand the context of the wider network both upstream and downstream of where they

are currently working.

Desktop

Establish the source of power: It allows Operators to quickly establish the source(s) of power

currently energising each network asset. Desktop

Access to asset historic information: It enables Operators to quickly access historic information

for each asset including load/voltage curves. It is possible to overlay historic and real time

information showing the current performance of an asset relative to its histor ical one.

Desktop and Mobile

Annotations on network asset: It provides the Operator with the ability to attach descriptive

text. Desktop

Alarm and event management: Operators have access to a comprehensive Alarm and Event

Management module that provides a consolidated view of all events on the system, including

SCADA alarms, metering events, etc.

Desktop and (Mobile10

)

Use of historic values: The LV NMS uses historical values (for instance, maximum values during

a period) to support network planning and development. Desktop

Network switching: Online update of network connectivity with planned jobs and outages from

both the Desktop and Mobile solutions. Temporary connections (i.e. Cuts and Jumpers), with

the real geospatial layout of the temporary assets in the field, are registered graphicall y and

their connectivity updated.

Desktop and Mobile

10 From the Mobile solution it is possible to visualise the smart meter events on the diagram.



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Capability name Desktop / Mobile

Restoration decision support: Selection of the actions to restore service supply, checking the

real time and historical values of power and voltage in the affected feeders and other feeders

that can assist the restoration process.

Checking the success of restoration in the field by querying the status of the smart meters of the

potentially affected Consumers and supervision meters.

Desktop and Mobile

Analysis of distributed generation: Specific analysis of distributed generation along LV feeders,

with the possibil ity of issuing voltage settings. Desktop

The UPGRID LV NMS solution has been built upon a prior LV prototype (deployed under the Bidelek

Sareak project11) and extends the interfaces and capabilities. During the demonstration implementation

the network area was extended (Figure 9) and the LV model has been completed including components

attributes in conformance to the reference CIM standard model.

3.2 EVALUATION

The LV NMS solution has been evaluated for over 6 months during normal operation of the LV network.

The scope presented in this section is based on the data loading process of the LV network area shown

in Figure 9 and the analysis of 583 LV incidents registered in the LV NMS. The bulk of the incidents are

related to issues related to SS fuses, feeder fuses and connection in LV risers (“botellas” in Spanish). 52

out of the total number of incidents have been managed by Field Crews using the Mobility tool). These

incidents are those managed by the staff who received the training course about the system and within

working hours. The incident data collected has been also included in an Excel sheet for facilitating its

analysis, see Figure 16.

For operational testing a total of 6 Mobile devices has been deployed. 4 units for the two Field Crews

equipped in the demonstrator (2 in Bilbao and 2 in Baracaldo areas), and 2 devices for internal testing

and monitoring purposes. The Desktop solution has been used by 2 people in Bilbao and 1 in Baracaldo.

Different training courses12 (end 2016, start 2017) have been carried out for the LV NMS users before

placing the solution in operation. Field Crews and control room staff have different privilege access on

to the Desktop solution. Experiences and feedback from them have been collected in order to identify

future enhancements based on the field use of the tool. In general terms the LV NMS has been

favourably received based on the surveys distributed among the participants. Moreover, the feedback

received during the courses and while is being in use, demonstrate that end-users13 are motivated and

willing to continue using the solution. This is a good indication of the usefulness of the system and paves

11 The Bidelek Sareak project is the demo base for the UPGRID Spanish demonstrator (http://bidelek.com/)

12 End of 2016 and beginning of 2017.

13 In this context, end-user is referred to LV operation and maintenance people who used the LV NMS (Desktop and Mobile solution).

http://bidelek.com/



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optimistically the ambition of extending the LV NMS deployment to other LV network areas in a near-

future as envisaged at the beginning of the demonstrator.

FIGURE 16: EXCEL SHEET EXTRACT WHERE LV INCIDENT INFORMATION HAS BEEN RECORDED FOR BEING ANALYSED FOR

EVALUATION PURPOSES

BASED ON THE DATA GATHERED AND EVALUATION CHECKS PERFORMED DURING THE OPERATIONAL USE OF THE LV NMS

IN THE DEMONSTRATION AREA, THE MAIN TOPICS THAT HAVE BEEN EVALUATED ARE PRESENTED IN THE SUBSECTIONS

BELOW. THIS STRUCTURE ALSO FOLLOWS THE LIST OF USE CASES DEFINED IN [2]: MAINTAIN LV DIAGRAM, INTRODUCE

TEMPORARY CHANGES, MANAGE UNPLANNED LV INCIDENTS, MANAGE PLANNED LV WORKS, INVESTIGATE LV INCIDENTS,

RECONFIGURE LV FEEDER AND CREATE LV INCIDENT OR ALARM FROM SMART METER EVENTS. DETAILED DESCRIPTION

AND TESTS OF THE INDIVIDUAL CAPABILITIES (

Table 5) developed in the LV NMS that support these topics were done during the elaboration of [2]. For

each of these topics, a series of specific improvements are pointed out as well which are linked to

business benefits processes.

3.2.1 SOUND LV NETWORK DIAGRAM GENERATION

The data importing validation has consisted in checking that the graphical representation in the LV NMS

matches with the GIS information. To perform this check, a number of randomly selected SSs were used.

The validation process has been done manually since it has been the first time this kind of data loading

was performed in Iberdrola. This, together with the fact that not only the GIS information is represented

graphically in the LV network diagram generated in the demonstrator, has made the testing process



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even more laborious. This additional information has been added to enhance the value of the resulted

model.

The LV network was loaded in LV NMS using CIM files. The CIM mechanism only allows the export of

connected elements in a circuit. Therefore, any exported element will be properly connected to the

correct elements upstream.

A series of main aspects have been examined to validate the correctness of the data importing process

following a kind of check list. This counts the new information not included in the GIS: LV feeders are not

physically represented and SS internals are not available in that system.

Check that LV feeders are connected to the correct LV switchboard (there are two colours

depending on the feeder voltage level. Each LV switchboard should have circuits with feeders of

the same colour).

Checks that all LV feeders (with their FBs) included in the GIS appear in the new LV network

diagram as well.

Check that LV feeders are not crossed among them.

Connectivity check. From FB to their corresponding distribution transformer.

Auto-transformer check. In order to check that they are properly connected.

Load break switch (“cajas seccionadoras”, in Spanish) check. To ensure its position is properly

placed on its corresponding network route.

Association between feeder and network routes (trenches) check. To ensure that cables are

properly associates to their network routes.

Connected supply point (FB) check. To check the number of supply point corresponding feeder.

Check for tracking total number of exported objects to the LV NMS.

Most of the cases checked have been well represented in the LV network diagram (e.g. Figure 17). This

means that the algorithm created for overcome the lack of graphical representation for feeders and SS

interiors have performed well in the demonstrator. The network diagram was not manually edited after

the automatic load from CIM. Given that network is being incrementally updated, all manual editing

would be lost when loading the next incremental update on the LV NMS. This highlights the reliability of

the algorithm developed to model the LV network. Moreover, descriptive attributes that were selected

to be displayed in popup windows associated to network elements are shown correctly based on the

comparisons done with the information in GIS.

Table 6 present a summary of ratios related to the goodness of the automatic data importing process

achieved during the first data loading considering the demonstrator area. These ratios, although not

high, would be permissible values taking into account the novelty of the process and the developed time

on the interface during the demonstrator. However for near-future data uploading, considering the

solution into operation should be close to 99%.



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TABLE 6: DATA IMPORTING RESULTS AFTER THE FIRST LOAD

SSs loaded successfully in the LV NMS solution 2.154 (77% success rate)

FBs loaded in the LV NMS solution 50.994 (90% success rate)

Data loading time (full demo area network) 7 days to export the CIM files from Model Integrator [1] and import them into the LV

NMS

FIGURE 17: EXAMPLE OF A SS INTERIOR SCHEMATIC SUCCESSFULLY GENERATED. VALIDATION BETWEEN GIS

INFORMATION (ABOVE) AND LV NMS NETWORK MODEL (BELOW)



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Moreover, smart meter did not reside in the original GIS system and were loaded separately and

automatically into the new LV network diagram adding additional graphical information about the type

of Consumers [1] (e.g. Figure 74, number of Consumers, existence of generation, sensitive consumer

and single or three phase smart meter). The validation check has consisted in comparing the loaded data

with registers on the SIC and GIS. This has been done with a number of cases chosen randomly. No

errors were identified.

TABLE 7: DATA IMPORTING RESULTS

Number of distribution transformer supervision meters loaded 3.083

Number of Consumer smart meters loaded 372.416

During the evaluation of the data importing process result, some issues were identified and reported for

either being quickly solved or taking into account for future LV network diagram loading. Some

examples are presented next. In Figure 18 it is possible to observed how line 6 (400 V) is connected to

an incorrect LV switchboard (231 V) after the data loading; and Figure 19 shows the case on a missing LV

feeders and its associated FBs. In some punctual cases, it was observed that certain FBs lacked of their

geographic coordinates on the corresponding data base table.

FIGURE 18: EXAMPLE OF LINE ASSIGNED TO AN INCORRECT LV SWITCHBOARD. GIS INFORMATION (ABOVE). LV DIAGRAM

GENERATED FROM GIS DATA (BELOW)

The auto-transformer check has allowed identifying issues in their representation. It is worth

mentioning that this kind of transformers where not included in the GIS. The needed amendments were



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implemented refining the graphical representation of these elements inside the SSs. Feedback was also

received from field about some missing lines or not exported data.

FIGURE 19: EXAMPLE OF MISSING LV FEEDER AFTER THE DATA IMPORTING

During the process of correcting wrong cases, it was identified the need of testing specific elements

faster without waiting for a new network loading. The latter is because data exporting process is

creating CIM data based on SSs, so it is possible to specify a specific SS or a set of them to export. But

import process from legacy systems, such as the GIS used in the demonstrator, was getting the whole

network for an area, which is usually composed of thousands of SS. Therefore, it was necessary to speed

the import process up just creating a new approach that extracts specific SS elements, its corresponding

circuits and related elements only. In this way, the same algorithm used for the import process ca n be

run, but allowing getting just the substation selected. In this way, this extraction approach gets any



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related element to a specific set of SS, creating a new set of files in the original format created from GIS,

but containing required elements only.

It is worth mentioning that in the demonstrator two different versions of the system have co-existed:

one for operation and one for development purposes. Taken into account all the information collected

during the evaluation, the incremental export process was modified to add these elements and resolve

the issue when possible. While the incremental load process was tested, they were confirmed as

resolved in most cases. From the manual evaluation process, issues related to 25 SSs were identified as

incorrect, and from these issues, they all were properly resolved after a subsequent incremental

import/export execution (in a development environment). This means that the new success ratios in

future network data loading should be closer to the desired ones for getting the process into production

(i.e. almost 100%).

One lesson learnt during the tests is that, since the LV network of the demonstrator includes more than

2.000 SSs, testing them all manually to verify if they are properly loaded is quite difficult and time

consuming. It is not possible to test every single combination of possible connected elements in the

network, since number of possible combinations is huge, especially for incremental load process. So,

identifying appropriate cases in order to maximise tested elements and minimise manual testing and

validation are required for future loading process.

Another result of the validation process is that the LV NMS developed in the demonstrator has been

able to manage successfully the increase of data arisen after approximately doubling the original

intended LV network extension covered by the system (see Figure 9). This demonstrates the scalability

of reliability of the network load process. Moreover, this extension has allowed identifying a series of

aspect to take into account before adding any other area:

Unique object identifiers: network areas to load could have duplicated object identifiers, in such a

case, some system should ensure that objects can be identified properly, even if they have

duplicated identifiers in their original repositories.

Exchange formats like CIM includes fields from different models: different areas could have

different data models, CIM schema should be extended to include them all if needed.

Data exchange formats should be the same: for the current demonstrator inputs from SXP format

(stands for Simple XML) and output to CIM format. An approach using different formats would

need to re-write several important pieces of code.

Table 8 seeks to reflect a summary of the main improvements process related regarding the sound LV

network generation and the business benefits that pose.

TABLE 8: SUMMARY OF THE PROCESS IMPROVEMENTS AND BUSINESS BENEFITS IDENTIFIED WITH THE SOUND LV

NETWORK DIAGRAM GENERATION

Improvements process related Business benefits - Diagram exchange availability in CIM data

format. - Visibility of the LV diagram.

- Operational real time view of the LV grid available within the organization.

- The better the quality of the diagram, the



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- Data quality improvement. - Module to extract specific parts of the LV

network from the Iberdrola’s original data (i.e. incremental data loading).

- Scalability of the load.

better efficiency in the operations and control.

- Future CIM compliance systems will be able to import the whole diagram or pieces of it (circuits).

- Loading specific parts of the network is very helpful for testing purposes, decreasing time required for incremental load tests.

3.2.2 LV DIAGRAM MAINTENANCE

The validation process regarding the LV diagram maintenance has been focused mainly on checking if

temporally network changes (i.e. cut and jumpers)14 have been registered correctly on the LV NMS

(network diagram and reports). To do that, the 52 LV incidents which have been managed using the LV

NMS Mobile solution have been reviewed, they all involved temporal changes. This temporally

operations are done in order to restore a consumer who has been affected by an incident on the LV

network as quickly as possible (later on they are removed when the permanent solution is carried out).

The same is done with switching operations. In this case, some incidents required, for example opening

/ closing LV fuse inside the SS (at the LV switchboard).

There are two scenarios:

1) The Desktop solution user needs to create the operation from the Desktop user and instruct (send)

the operation to the LV Field Crew who is supplied with a mobile device. Then the Field Crew

acknowledge and confirm on it. All information should be recorded graphically and in the

corresponding work log of the LV NMS.

2) The Field Crew is who create the operation without any Desktop user involvement. This means

that once the element status is modified at field it can be reflected (manually) on the LV network

diagram. When the operation is set as confirmed, the fuse is shown on the diagram reflecting its new

state and the new energisation status of LV feeders affected by that operation is also automatically

displayed on the diagram.

The second scenario was implemented based on the feedback received from LV NMS users during early

training courses during the development phase. Moreover, in both Desktop and Mobile, the user should

be able to search for all temporary operations and navigate to the diagram from each of them.

An example of the evaluation process is shown from Figure 20 to Figure 22. In these figures it is possible

to observe that the cut and jumper is sent by the Desktop user to the Mobile solution is registered

correctly and when it is performed by a Field Crew is also visualised automatically by the Desktop

14 Temporal elements (e.g. cuts and jumpers) are carried out on the field in order to quickly restore consumers who have been affected by an outage. These temporal elements remain for a short period of time (typically less than 36 hours) until a permanent fix can be carried on th e network.



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solution. While Figure 23 is one example monitored in real time when the Field Crew register graphically

the temporally change on the Mobile solution in one of the selected incidents.

FIGURE 20: RELATED CUSTOMER CALLS FOR AN OUTAGE

FIGURE 21: OUTAGE HISTORY FOR AUDITING PURPOSES



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FIGURE 22: SWITCHING LOG DETAILING THE TEMPORARY OPERATIONS TO RESTORE AN INCIDENT

FIGURE 23: THE SAME TEMPORAL ELEMENTS SHOWN IN THE MOBILE SOLUTION



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Figure 24 and Figure 25 present an example of the validation perform checking scenario 1 and 2.

FIGURE 24: FUSE OPERATED ON TABLET. THE FUSE ON THE RIGHT HAS BEEN REMOVED

Information is presented also in a tooltip state on the Desktop diagram and the visualisation indicates

the phases affected.

FIGURE 25: VISUALISATION ON DESKTOP DIAGRAM OF A REMOVED LV FUSE (THE ELEMENT NOT COLOURED ON THE RIGHT

HAND SIDE) AND THE LV CIRCUIT DE-ENERGISED (IN WHITE). A TOOLTIP DISPLAYS THE FUSE STATUS PER PHASE.

This functionality has been well valuated based on the feedback received from field. It is highlighted that

prior to the LV NMS solution these temporary operations were recorded on paper. By having a LV



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network and the ability to add these temporary operations from the Mobile device as they are carried

on the field, the recording of these operations is simplified and the LV network representation is more

accurate, reflecting the real time state of the network. Overall, the system complies with the

expectations.

Additionally, some enhancements have been proposed by the Field Crews after using the Mobile

solution to perform these operations:

The Field Crew informed that sometimes operations are carried out on the neutral cable. These

operations currently cannot be recorded or reflected on the diagrams except as a visual marker.

The LV NMS is not considering the existence of the neutral phase. In real O&M some field work

relies on the use of this phase for temporal solutions. Most of the neutral cable breakage create

overvoltage episode in the network what can even burn Consumer appliances.

When reconfiguring feeders, the Field Crew also expressed the need to easily identify the circuit

for given feeder on the diagram. The feeder name reflects the circuit but further opportunities

exist to allow tracing functionality from the Mobile device.

Being able to open/close fuses in FBs (most probably the system allows it but it was not

considered in the first specification and then not parametrised).

Being able to perform actions in the LV risers since it is one major focus of LV incidents. In this

case the LV risers are graphically represented but they are not operable (capability not included

in the current version of the system).

Table 9 seeks to reflect a summary of the main improvements process related regarding the sound LV

network generation and the business benefits that pose.

TABLE 9: SUMMARY OF THE PROCESS IMPROVEMENTS AND BUSINESS BENEFITS IDENTIFIED WITH THE LV DIAGRAM

MAINTENANCE

Improvements process related Business benefits

- Record switching changes to the network topology so that the LV diagram is operationally correct either by desktop or mobile interface.

- Record temporary changes to the network topology so that the LV diagram is operationally correct either by desktop or

mobile interface. - Visibility of planned work requiring de-

energisation.

- Accuracy of the LV sound representation - Accurate and timely recording of temporary

operations. - LV Field Crew can record the temporary

actions directly on the mobile device keeping the information stored and available for

other system users.

3.2.3 LV NMS INTEGRATION WITH EXISTING SYSTEMS: INTERFACES

The evaluations performed around this topic have been aimed mainly at checking the integration of the

data coming from the different source systems (see Figure 14 and Table 4) into the LV NMS. That is,

validate that the same information managed in by the source systems is the same that is used by the LV



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NMS and how the performance of the interfaces is. Each interface has been individually tested and left

enabled for the duration of the evaluation, over 6 months. Some interfaces have been executed just one

time (e.g. SIC) while others are active on line (e.g. OMS).

Overall, MV voltages, Consumer calls and spontaneous meter events, and the ability to poll the smart

meters and visualise the results were received in real time. Visual representation on the diagram of the

smart meter events has been achieved. This was accessible from both the Desktop and Mobile user. This

visual information provided the field engineers with a better understanding of the state of the network

in real time. Apart from punctual cases that were solved, the performance observed has met the

expectations. This is especially important for those that are executed in real time.

Validation 1: This evaluation has consisted on checking that measurements displayed in the LV NMS

correspond to those from the data source. In the case of MV voltages, the quality of the measurement

and the timestamps were checked against the data held in the MV SCADA system. Figure 26 and Figure

27 show an example of the validation performed. Other measurements have been checked against the

meter data management system (MDMS), for example, measurements of SS supervision meters. Figure

28 and Figure 29 show one of the cases checked15.

FIGURE 26: SS MV MEASUREMENT ON THE SCADA

15 Important to note that the S14 report (measurements from SS supervision meters) are hourly measurements while the measurement s on demand shown in the LV NMS network model are instant values. For this reason slight differences can be observed.



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FIGURE 27: SS MV MEASUREMENT ON THE SAME SS OF FIGURE 30 REPRESENTED ON THE LV NMS

FIGURE 28: MEASUREMENT REPORT ON SS SUPERVISION METERS EXTRACTED FROM THE MDMS



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FIGURE 29: SS SUPERVISION METER MEASUREMENTS (ON DEMAND) SHOWN IN THE LV NMS LV NETWORK DIAGRAM

THROUGH THE LV NMS-OMS-AMI INTERFACE

Validation 2: This evaluation has consisted in checking how the LV NMS registers as incidents on the LV

network diagram those outages reported by Consumers to the call centre. They should have been

logged firstly in the OMS and then passed onto the LV NMS. The calls should be mirrored in the LV NMS

and displayed on the LV diagram, providing visual information of where potential network issues might

exist. The Consumer call might automatically either generate an incident or be grouped with an existing

incident on the area. This information is also available to the Field Crews on the Mobile device.

The test consisted in the following procedure. First, selecting the LV incidents that responsible staff is

informed (backwards) about the happening by sms. Second, these incidents are traced in the existing

Incident Reporting System where it is possible to see the Consumers and events associated to them.

Third, telephone numbers are traced in the LV NMS to check that the same calls have been associated to

the same incident in the LV NMS.

Based on the 583 real LV incidents reviewed, almost 100% of the cases have been reposted correctly.

Only in one case a strange behaviour was observed without being able to replicate the scenario.

It has been observed that calls from public services (e.g. firefighters, SOS, etc.) are not associated to a

specific FB because they have not an electricity supply contract associated to. It would be necessary to

find a way to overcome these cases.



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FIGURE 30: CONSUMER CALL DISPLAYED ON THE DIAGRAM ALONG WITH INCIDENT NEAR THE FUSE BOX SYMBOL

Validation 2: Similarly, spontaneous events from SSs (distribution transformer supervision meters) or

Consumer smart meters provide useful alerts on possible outages or quality of supply issues on the LV

network. Depending upon the type of event, the LV NMS might handle the event differently. SS meter

events should be visualised on the diagram and they automatically generate a new alarm within LV

NMS. It has been proved based on field records that 751 incidents have been recorded in the LV NMS

triggered by smart meters events. Some of them are also associated to incidents triggered by Consumer

calls.

FIGURE 31: CONSUMER SMART METER EVENT DISPLAYED ON THE DIAGRAM AS A PSEUDO CALL NEAR THE FUSE BOX

SYMBOL



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The validation check has confirmed that the system is able to grouping Consumer calls and smart meter

events. Some cases have not work as expected (e.g. missing events associated to the corresponding

incident or events of the same smart meter but in different moments are associated to the same

incident). This has been observed comparing the grouping performed by the LV NMS and the Incident

Reporting System. Possible causes that are being analysing: configuration issues or algorithm

performance. Moreover, based on the evaluation, it is concluded that the process could still be

enhanced to perform a more refine prediction of the LV incident location. This would entail identifying

the first LV network element in common to all calls and smart meter events. It is consider that this

feature of the tool present an interesting potential for adding value to the Consumers (e.g. DSO can

know quicker the incident existence, it can initiate faster the restoration process, and most probably

shorter the incident time to the Consumer) then it will further explored.

The feedback received from the Field Crews based on the experience collected after managed 52 LV

incidents with the Mobile solution says that being able to perform smart meter measurements on

demand (Figure 72) is a useful feature to:

check if a smart meter has service.

check if a LV incident affect one phase or to the full feeder.

In some case they have reported that this capacity has proved to be useful to locate LV incidents

on the LV network.

Some users have pointed out that it would be good to be able to perform consults to retrieve

information that has not been contemplated in the demonstrator interface architecture approach

(Figure 14). This would allow, for example, consulting the maximum current per feeder before

performing temporally filed works (i.e. cut and jumpers). In this way it could be possible to check it

feasibility (i.e. identify in advanced congestion issues in the affected feeders). Consequently, as a next

system enhancement, it is thought that integrating the aggregated load curves at FBs and feeder level

would be useful for Field Crews. Moreover, user feedback highlighted the length of time required to

receive a polled smart meter values (approximately 3 minutes). An opportunity exists to interface

directly to the AMI system to shorten the time of reply. In the demonstrator it was decided to use the

interface OMS-AMI because it existed before and it was considered as an opportunity to build the

architecture over that infrastructure.

As evaluation of the new analytics tool designed for reporting user friendly data from the LV NMS

databases and other data sources, two geospatial analyses (GSA) have been implemented. These

analysis access databases [1] (spatial data about SSs or FBs) and LV NMS (non-spatial data about smart

meter events or incidents) and combine them to provide useful geospatial reports. Figure 32 and Figure

33 show examples of the customised geospatial analysis.



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FIGURE 32: GEOSPATIAL ANALYSIS TOOL (GSA) REPRESENTATION EXAMPLE. LEGEND: SS = STARS, FUSE BOXES = CIRCLES

WHICH SIZE DEPEND ON THE NUMBER OF SMART METER EVENTS, LV FEEDERS = GREY SEGMENTS)

FIGURE 33: GEOSPATIAL ANALYSIS TOOL (GSA) REPRESENTATION EXAMPLE. SS’S ARE CIRCLES WHICH SIZE DEPEND ON THE

NUMBER OF LV NMS INCIDENTS AND GRAPHS WITH INCIDENT CATEGORIES CLASSIFICATIONS



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Table 10 seeks to reflect a summary of the main improvements process related regarding the LV NMS

integration with other systems and the business benefits that pose.

TABLE 10: SUMMARY OF THE PROCESS IMPROVEMENTS AND BUSINESS BENEFITS IDENTIFIED WITH THE LV NMS

INTEGRATION WITH EXISTING SYSTEMS

Improvements process related Business benefits - Integration with MV SCADA in the diagram

visualization (e.g. Figure 66). - Integration with MV OMS in the diagram

visualization. - Integration of Consumer call information in

the diagram visualization. - Integration of smart meter event information

in the diagram visualization (e.g. Figure 68). - Integration of smart meter instantaneous

values (e.g. Figure 70 and Figure 72). - Integration with MV system (energised state

of the distribution transformer, e.g. Figure 67).

- Integration with Iberdrola’s OMS system to report incident information when closing the incident.

- Integration with the Planned Work System (GIRED) (e.g. Figure 73).

- Integration with Maintenance Work System (GOT) (e.g. Figure 71).

- Near real time measurements will provide a

more informed view of the state of the network to the user (both Desktop and

Mobile). - Enhancement of the decision making process

and therefore, the QoS. - Reduce the incident resolution time and

therefore, the QoS. - Planned work also managed from LV NMS.

The visualisation of the planned and unplanned work on the same tool provides a better understanding of the state of the network to the LV NMS user.

3.2.4 LV INCIDENT MANAGEMENT: LV O&M

The validation process regarding LV incident management has been focused on analysing the 583 LV

incidents registered in the LV NMS and the 52 LV incidents managed by Field Crews with the LV NMS

Mobile solution. All information related to these incidents has been extracted into an Excel sheet (Figure

16) for an easier data management. The main issues explored are as follows:

Period of time between an incident creation due to a smart event registration and the first

Consumer call related to that incident.

Clearance of the LV incident responsibility.

Total LV incident duration.

Improvement on the LV incident scope (reports).

As evaluated in section 3.2.3, the LV NMS is able to create a LV incident register with a Consumer call

and/or a smart meter event. In the latter case, the incident could have happened without being known

by the Consumer (e.g. for being out of home). An earlier start to restore the electricity, and even the

information (about the incident) that, under this scenario, the DSO could be able to provide to the



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affected Consumer when calling reporting it, are examples of values added that the demonstrator

developments can offer to Consumers. Based on the analyses of the registered incidents that have

events and calls grouped (30 incidents), this differential time that would be saved on the total time of

the LV incident would be, in average, 36 minutes (min.).

Not all calls received from Consumers are related to LV incidents under the responsibility of the DSO

(e.g. downward the smart meter). The call centre pre-filter them but still some of them arrived to the

DSO. The capability developed in the LV NMS Mobile solution to perform smart meters and supervision

meter measurements on demand (ping) allows Field Crews to determine if the incident gets under their

responsibility. This avoids unnecessary Filed Crews displacements in case the incident is not

responsibility of the DSO, what means a saving in time and allows a much optimal use of resources,

having Field Crews much available to respond to incidents. This should provide better service to the

Consumer. Based on the demonstrator experience, 22 out of the 52 incidents managed with the Mobile

solution were not responsibility of the DSO. Using the on demand request of meter measurements, the

Field Crew avoid all these displacements.

In Chapter 2 and in the present one (in more detail in [1][2]), a series of LV NMS capabilities have been

described and how they can impact of the incident time restoration explained. Based on the operational

experience of using the developed system to managed LV incident during the demonstrator, it has been

observed that this time have been reduced in 16 min. This value has been obtained comparing 30

incidents managed with the LV NMS Mobile solution and similar ones in both, season and description,

before using the LV NMS. It is worth mentioned that as time goes a more incidents are managed with

the Mobile solution, more accurate results can be obtained. Moreover, it is believed that the

implementation of the potential improvement received from system users during the demonstrator and

the ending of devices deployment ongoing and its affective integration into the system architecture will

improved even more this timing.

The accuracy on reporting Consumers affected per incident has been evaluated as well. 212 incidents

registered in the LV NMS have been compared with the same incidents but in this case how they would

have been registered in the current incident reporting system. Based on this analysis, the reporting

accuracy has been 32%16. It worth mentioned that this procedure would be improved in the short-term

when the Iberdrola connectivity solution is fully deployed at field. Moreover, tests performed on the

reporting generation process, have allow observing that the consumer information on these reports are

not filled automatically. This is an issue that need to be solved to avoid manual work.

From the feedback received from users who use the Mobile solution at field the following

improvements are identified: being able to record operations on the neutral cable (see section 3.2.1)

16 It has been calculated taken the total time per incident, multiplying the number of Consumers reported (“ambito” in Spanish) by the time of the incident. The result is added up per each incident and divided by the total number of Consumers reported as affected in all incidents (based on the incident reporting system). This is done using the reports before UPGRID and those generated in the demonstrator using the LV NMS.



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and connect Consumers between two phases. In real O&M some field work relies on the use of this

phase for temporal solutions. Moreover, incorporating the capability of performing DPF in the Mobile

solution would provide Field Crews with more flexibility to analysis different scenarios to determine the

most convenient alternative to restore the electricity supply after an incident.

Table 11 seeks to reflect a summary of the main improvements process related regarding the LV

incident management and the business benefits posed.

TABLE 11: SUMMARY OF THE PROCESS IMPROVEMENTS AND BUSINESS BENEFITS IDENTIFIED WITH THE LV INCIDENT

MANAGEMENT

Improvements process related Business benefits

- Manage unplanned LV Outage.

- Manage planned LV Outage. - Investigate LV Outage by requesting on-

demand smart meter values. - Incident completion report. - Feeder re-configuration: Restore supply by

bridging supply from a neighbouring feeder. - Empower field engineers with a mobile

application to access the system. - LV network geospatial analysis and reporting

(e.g. Figure 32, Figure 33 and Figure 75).

- Determine cause of outage and restore power as quickly as possible.

- All relevant information of planned outages will be shown on LV diagram.

- This will speed up the outage investigation and its restoration. This along with the

granularity of Consumers affected per supply point will decrease the Consumers per

minutes lost. - To compare quality of the service (QoS)

against existing system. - Have reports with clear and accurate

information for improve strategic business

decisions.

3.3 OPPORTUNITIES

New opportunities have been identified after analysing the operational field experience of the system

which is as follows:

Using the UPGRID Spanish demonstrator as a reference, extending the network area (i.e. add new

regions or cities) covered by the LV NMS is possible, but some issues identified during the use of the

system should be managed in advance.

It could be possible to improve the incremental data load process identifying in advance which SS

have been modified by users in UPGRID. In this way, a new process could use this information to

filter specific network parts for incremental load (such module for filtering parts of the network has

been developed already in the demonstrator).

Periodic Consumer smart meter readings could be utilised to create load profiles in the LV NMS

system. This could be a monthly update where data collected for a specific month would be fed into

the existing load profile for the associated FB for that month. A better modelling of the load on the

LV network will lead to more power flow studies accurate results.



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During the demonstrator the field work orders (e.g. notifying the closer Field Crew to manage a LV

incident) have been dispatched to the LV NMS Mobile devices manually. An opportunity exists to

automate this process. This should lead to efficiency improvements.

The collaborative methodology between Field Crews could be enhanced, allowing dispatching and

taking back field work orders amongst them using the LV NMS Mobile device without inputs from

the control centre. Being the auto-dispatching of LV field works on of the most relevant opportunity.

That is, Field Crews will receive automatically LV the field work request automatically without the

intervention of the control dispatch. This feature, together with previous points, would enhance the

distributed O&M LV business process distributed approach (see section 8.1).

Implement enhancements to existing interfaces with Iberdrola own systems to allow the

incremental updates of Consumer and meter data, which does not reside in a GIS database.

New functionality could be made available to Field Crews on the LV NMS Mobile solution such as the

ability to run power flow studies and create annotations on the LV diagram.

New functionality could be made available so that LV NMS system automatically gathers

instantaneous smart meter values when incidents are predicted on the network (as a result of

Consumers calls or smart meter events received).

The architectural design of the interfaces (developed in the demonstrator) that allows the LV NMS

interaction with existing Iberdrola systems would need revisiting if this were to be extended. For

example, in order to request spontaneous smart meter values, the interface LV NMS - AMI is not

directly stablished to the latter system, adding a delay of approximately 2-3 minutes in getting back

the smart meter response.

New data sources can be easily added to the analytics tool geospatial so reports can be updated with

new data very quickly. For example, they can be updated with historic data generated along LV NMS

production use, generating more accurate and useful reports.

3.4 CONCLUSIONS

The quality of the GIS source is a requisite for a successful import of the LV network. Using CIM, which

loads LV network circuits rather than individual components, the correct connectivity of the elements in

the source GIS is vital. Based on the demonstrator experience, where the connectivity has some

inconsistencies, the elements are not loaded on the diagram and can lead to a substantial amount of re-

work and analysis. Sanity checks on the GIS source should take place prior to the network loading

exercise, and continue along this iterative process.

After the CIM files were loaded in the LV NMS, no manual tidy up of the imported network took place.

The network shown is how it was loaded in CIM, with the ability to run traces straight away on a newly

loaded circuit. This highlights the robust design of the modelling process.

In order to speed up the incremental updates of the LV network the GIS source should be able to

produce the ‘delta’ of the changes as they happen. Having a modelling tool where different snapshots of

the GIS system are loaded and compared in order to produce the ‘delta’ has proven difficult and time



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consuming. The source GIS system should have this capability if incremental updates of the LV network

were needed. The large number of SSs loaded allows having a realistic estimate of the effort involved

when extending the geographical scope of the LV network, relying on similar quality of the GIS data.

Given that the LV network extension covered by the LV NMS was doubled during the life of the

demonstrator (Figure 9), it has been demonstrated the capacity to scale this solution.

The deployment of multiple interfaces between LV NMS solution and Iberdrola’s existing systems

provides the LV NMS user with relevant information such as planned work, MV measurements, smart

meter events and smart meter polled values. Some of them are real time interfaces and are reflected on

the LV diagram. The LV NMS user, either using the Desktop or Mobile solution, has a full understanding

of the real status of the LV network at any point in time. The LV diagram conveys visual information to

the user who is better equipped to take decisions regarding the network operation. Plus the ability to

poll the smart meters on site from the mobile device enhances the information. Moreover, having a real

time LV network, where temporary operations like cuts and jumpers are maintained and gives an

accurate reflection of energised and de-energised sections of the network for instance helps the O&M

of the LV network. The granularity of the consumer supply points allows the system to accurately

predict the number of Consumers affected after LV incidents. GSA allows O&M responsible to generate

new spatial reports with multiple data sources. This is an improvement that can be used to take more

justified business decisions or a better LV network management.

The results obtained so far regarding LV incident management using the LV NMS show encouraging

insight to back the expectations articulated at the beginning of the demonstrator and there is still room

for improvement and continue working in this direction. Thanks to the feedback received from users

who has used the solution, the system will be improved adding new capabilities.



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4. USABILITY OF LV SMART METERING PRIME TECHNOLOGY

FOR REMOTE CONTROL

The main objective of this chapter is to report on the usability of the LV smart metering PRIME

technology for remote control. First, the introduction provides information to understand main aspects

developed in the demonstrator with this regard. Second, field test results and conclusions are

presented. Annex II, Annex III, Annex IV and Annex V contain more testing details.

4.1 INTRODUCTION

The Spanish demonstrator has two goals in this area. On the one hand, to define the architecture that

allows multiple applications (smart meter management and remote control) on top of a PRIME

subnetwork. On the other hand, to deploy a PRIME Management system (software solution) to monitor

the basic performance parameters of a PRIME subnetwork.

The main result has been the implementation of LV infrastructure remote control over PRIME. This

deployment is based on two lines of work: PRIME as a multiservice subnetwork and PRIME as a

subnetwork than needs to be monitored. It is worth mentioning that the monitoring capability is the

initial requirement to integrate remote control over PRIME.

In the scope of the demonstrator a new generation of devices has been designed and developed aimed

at including, in a compact device which can be plugged in the LV network, IP capabilities over PRIME

network. This equipment is named PRIME Gateway (GTP)17. One of the most interesting applications

provided by IP traffic over PRIME in LV network is remote control. Based on laboratory test results

already conducted [1], it would be feasible to use current PRIME network in order to transmit AMI

(metering) and remote control traffic. Field tests of section 4.2 pretend to confirm these results.

Three different use cases [2] are identified in order in order to evaluate multiservice PRIME subnetwork

performance:

TABLE 12: USE CASES FOR FIELD TESTING

Use case Objective

Use case 1: SS with existing Remote

terminal Unit (RTU)

Measuring the performance of an existing RTU, previously installed in a SS, but now replacing the current transmission media (Ethernet) with PRIME.

This means that the RTU traffic (IEC 60870-5-104) is transported over PRIME. Figure 34 and Figure 35 show installation details.

17 These GTP devices are currently in homologation and acceptation phase. This is required to be fully integrated on the grid. Then, they can be only powered-on for punctual testing within the demonstrator use case described in this section.



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Use case Objective

Use case 2: SS without remote

access

Testing the IP over PRIME capability in terms of bandwidth of IP over PRIME. This would be the transmission mean for the information exchanged

between the AMI Head System and the AMI data concentrator in the SS. This simulates the case of a SS that does not have enough GPRS/3G coverage to let the router establish a good connection with the AMI Head System.

Use case 3: LV backup feeder smart-

switch application

Testing a remote control application to be applied for LV backup lines

switching from one SS to an alternative one. It is referenced as LV backup feeder smart-switch application. This is an alternative future approach that would be applicable in scenarios where mesh LV networks are available.

FIGURE 34: SS NETWORK ARCHITECTURE WITH AN EXISTING RTU (USE CASE 1). INITIAL SCENARIO (ON THE LEFT).

SCENARIO THAT INCLUDES GTPs TO TEST REMOTE CONTROL TRAFFIC OVER PRIME (ON THE RIGHT). CCT = DATA

CONCENTRATOR, IBD = IBERDROLA

FIGURE 35: PRIME GTPs INSTALLED IN A SS



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PRIME PLC specification covers different convergence sublayers definition so different types of traffic

sending are optimized. PRIME 432 convergence sublayer is the most widely deployed as it covers AMI

traffic. Now, there is another sublayer, IPv4 convergence sublayer that was originally defined in PRIME

to send multi-service data. This means that it was left open for future traffic requirements within the

PLC channel. Now, in the scope of UPGRID project, it has been made the development required in order

to support this IP over PRIME transmission (that was already technically described in the specification).

And going one step further measured the performance of this multi-service data transmission option

and how did it impact in current AMI traffic being exchange. Over this development, as a particular case

of multi-service data, remote control traffic is transmitted. For tests oriented to this specific service it

was found during the project that this profile needed specific capabilities that in order to ensure

interoperability will be agreed and specified within the PRIME Alliance [14] based on the ticket opened.

The PLC PRIME subnetwork deployed for smart metering applications is a communication channel that

needs to be monitored. This requirement becomes even more important in the context of the PRIME

multiservice network when new applications are integrated on it. Then, the demons trator has extended

the PRIME subnetwork monitoring capabilities as follows:

Software (SW) evolution that has been installed in 40 AMI data concentrators devices covering

around 14.000 smart meters in the demo area. The SNMP PRIME Management Information Base

(MIB) has been defined and implemented successfully.

A SNMP web tool (i.e. Network Management System) for collecting MIB has been specified,

designed, and installed at Iberdrola premises. It gathers all relevant information from the PRIME

PLC subnetworks connected to.

FIGURE 36: SCREENSHOT OF THE SNMP WEB TOOL INTERFACE - DATA ACCESS SHOWING NODES CONNECTED IN THE

DEMONSTRATION AREA. NUMBER OF TERMINALS (IN GREEN). NUMBER OF SWITCHES (IN BLUE)



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FIGURE 37: SCREENSHOT OF THE SNMP WEB TOOL INTERFACE – CONFIGURATION MENU

The rest of the chapter is divided in two parts in order to evaluate separately the two main goals of the

Spanish demonstrator regarding the PRIME functionalities as introduced above.

4.2 MULTISERVICE PRIME SUBNETWORK (LV REMOTE CONTROL OVER

LV SMART METERING PRIME TECHNOLOGY): EVALUATION AND

CONCLUSIONS

The goal is to define an architecture that allowed multiple applications (e.g. smart meter management

and remote control) on top of a PRIME subnetwork. This section describes what this approach is about,

the benefit compared with previous solutions, tests performed and results of the field deployment done

within UPGRID Spanish demonstrator. The chapter ends with an analysis of the main benefits and its

applicability based on the results obtained. Annex II and Annex III complement the tests with more

detailed data and information.



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4.2.1 LV CONTROL TRAFFIC OVER PLC PRIME - FIELD VALIDATION CONDITIONS

In the scope of the demonstrator a new generation of devices has been designed, named PRIME GTP.

This is a compact device which can be plugged in LV network that in order to enable a multiservice

PRIME subnetwork, implements IP capabilities over PLC PRIME. This IP traffic over PRIME functionality

enables the remote control service that needed to be deployed within UPGRID project. Once validated

in laboratory, field scenarios (Table 12) were selected in order to transmit simultaneously AMI

(metering) and remote control traffic over the same PRIME network.

This deployment requires the installation of multiple PRIME GTP devices . The number and topology of

these deployments are described in the following sections.

In order to clarify field deployment conditions, it is worth noting that permanent installation of devices

in the Iberdrola’s LV network requires a previous homologation and acceptation process. The GTPs are

prototypes developed within the scope the UPGRID Spanish demonstrator and they are in the

homologation phase. Therefore once they were installed, they have been only powered-on for testing

purposes within the project scope. Also, two UPGRID portable testing cabinet types have been designed.

Finally, the LV remote control deployment plan designed initially needed some adjustments. It has

implied integrating these new capabilities into an AMI system already developed and in operation.

Moreover, field SCADA system accessing RTUs have some security conditions that need to be met.

Therefore, this implied some addressing, configurability and remote control traffic exchange limitations

for UPGRID project deployment. Test setups and results are described below.

4.2.2 UPGRID CABINET FOR LV REMOTE CONTROL - FIELD DEPLOYMENTS

4.2.2.1 UPGRID CABINET MODEL 1: INTEGRATING A PAIR OF PRIME GATEWAYS (GTP)

This first cabinet model is used for use case 1 which aim is to measure the performance of an existing

RTU, previously installed in a SS, but now replacing the current transmission media (Ethernet) with

PRIME. Figure 38 shows the portable cabinet type 1 installed in field deployment that has been used for

the LV remote control over PRIME field test scenarios.

Internally, this cabinet has two PRIME base node (PBNs) installed, one of them has a master (base node)

role and the second one has a slave (service node) role. In the scope of UPGRID project the test replaces

the local Ethernet communication with the RTU with an IP over PRIME connection enabled by the two

PBNs installed in the UPGRID portable cabinet.



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FIGURE 38: PORTABLE CABINET TYPE 1 INSTALLED IN FIELD DEPLOYMENT

4.2.2.2 UPGRID CABINET MODEL 2: INTEGRATING A SINGLE PRIME GATEWAY (GTP)

This second cabinet model is used for use case 2, whose aim is to simulate SS locations where the SS

does not have enough GPRS/3G coverage to let the router establish a good connection with the AMI

Head System. In this context GTP capabilities provide an IP connection over PRIME network to an

alternative location (such as a meter room nearby), from which the GTP will be the one making the

bridge to GPRS/3G connecting with the AMI Head System. Figure 39 shows the portable cabinet type 2

installed in field deployment that has been used for the LV remote control over PRIME field test

scenarios.

FIGURE 39: PORTABLE CABINET TYPE 2 INSTALLED IN FIELD DEPLOYMENT

Two GTP devices with service and base node roles

Mounted in a portable cabinet

One PBN GTP device configured as base node



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4.2.3 USE CASE 1: SS WITH EXISTING RTU - RESULTS, PERFORMANCE AND TOOLS

4.2.3.1 TEST SETUP AND CONDITIONS

This scenario has been selected in order to measure the performance of an existing RTU, previously

installed in a SS, but now replacing the current transmission media (Ethernet) with PRIME. This means

that the RTU traffic (IEC 60870-5-104, hereinafter called 104) is transported over PRIME, instead of over

Ethernet.

In this scenario, RTU traffic and AMI traffic will be sharing the PRIME channel . RTU traffic is routed

through the GTP (acting as service node, slave role) via PRIME and AMI traffic from meters is managed

by the second GTP (acting as base node, master role). Tests under this scenario combine RTU traffic in

presence of AMI traffic.

FIGURE 40: BASIC UPGRID ARCHITECTURE OF REMOTE CONTROL OVER PLC PRIME TESTING

There are some requirements in order to select field locations for remote control over PRIME UPGRID

deployment. Two SS with a RTU already installed and integrated in the SCADA system were required.

These two SSs within the scope of the demonstrator area are selected, SS TORRE ABANDOIBARRA 2 and

TORRE ABANDOIBARRA 1.

In the scope of UPGRID project the first step consisted in replacing the local Ethernet communication

with the RTU with an IP over PRIME connection enabled by the two GTPs installed in the UPGRID

portable cabinet. The designed architecture can be seen in Figure 41. GTP A and GTP B have been

installed in the field using a cabinet specially designed for the UPGRID project, cabinet type 1 described

in the section above. It includes GTP A, which is connected to Ethernet port of the SS switch, and GTP B,

which is connected directly to the existing RTU.

Remote control in the Secondary Substation – Original topology

Switch RTU

Ethernet

Remote control in the Secondary Substation – UPGRID test control over PRIME

Switch RTU

GTP Role: base

GTP Role: service

IP over PRIME

LV PLC

Ethernet Ethernet

Remote

control with SCADA

Remote control with

SCADA

UPGRID portable cabinet type 1



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FIGURE 41: UPGRID INSTALLATION AT TORRE ABANDOIBARRA 2 SS

FIGURE 42: IMAGES OF THE REMOTE CONTROL TRAFFIC TEST PERFORMED AT TORRE ABANDOIBARRA 2 SS

It is worth mentioning that the RTU simulates any LV controllable device in the grid because, at the

moment, there are not such devices in the demonstrator area. Then, this is a proof of concept.

Although the designed architecture included remote access from the operation SCADA to the RTU, there

were some addressing and configurability limitations in the deployment systems that made this

approach unfeasible. A summary of the implemented measures required for the tests are presented

next. They are divided in two parts based on the test objectives. Test plan and execution is detailed in

Annex II.

Part_1: Analysis of PRIME PLC performance sharing AMI traffic and IP over PRIME traffic. The

goal of this initial test plan is to evaluate the channel usage sharing the media between AMI data

and remote control data.

- Measure_1: Force AMI traffic and check that results are successful. First iteration is done

without IP over PRIME traffic in parallel. AMI traffic is forced uploading an eXtensible

Markup Language (xml) cycle to the AMI data concentrator.

- Measure_2: Force IP over PRIME traffic and measure the maximum delay of Internet

Control Message Protocol (ICMP) traffic sent. First iteration is done without AMI traffic in

parallel.

GTP B (role

service)

GTP A (role base)

RTU



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- Measure_3: Force AMI and IP over PRIME traffic in parallel and compare the performance

with the two measurements taken with only a type of traffic each time.

Part_2: Analysis of remote control 104 traffic exchange over IP over PRIME. - Measure_1: Force IP over PRIME traffic with ICMP packets to make sure the channel is

established.

- Measure_2: Connect the local SCADA to the RTU through IP over PRIME. This would validate

UPGRID concept for remote control traffic exchange over PLC PRIME. 104 control traffic is

starter although due to addressing limitation further exchange is rejected. Anyway,

bidirectional 104 traffic is exchanged and the concept is validated.

- Measure_3: Connect the local SCADA an RTU simulated in a second PC (WinPCPau18 test

tool).

4.2.3.2 TEST RESULTS AND PERFORMANCE

This section summaries the test results and the performance obtained at field.

Part_1: Analysis of PRIME PLC performance sharing AMI traffic and IP over PRIME traffic.

- AMI traffic in field locations selected with UPGRID GTP portable cabinet installed is

successful. When no IP over PRIME traffic is simultaneously sent, AMI performance is not

affected. This is the expected result and it proves that the implementation is correct and no

regressions are found.

- IP over PRIME traffic in field locations selected with UPGRID GTP portable cabinet forced by

ICMP packets is successful. Answer time with IP over PRIME traffic never exceeds 450

milliseconds (ms). This performance is stable in the time. This proves that multiservice IP

over PRIME exchange over UPGRID implemented GTP devices is successful.

- When both AMI and IP over PRIME traffics are forced to be exchanged in parallel the

performance varies. This test aims to evaluate this impact and confirm if the performance is

good enough for a further deployment. Based on the results presented below, traffic

exchange is successful and the concept is validated. Then, both types of traffic can coexist.

o IP over PRIME traffic with AMI traffic in parallel maintains the same latency 450 ms

with punctual packets arriving around 1.500 ms.

o The results of AMI readings during this test are also successful.

Part_2: Analysis of remote control 104 traffic exchange over IP over PRIME.

- IP over PRIME traffic with ICMP packets are exchanged successfully so the channel is

established. Under these testing conditions there is no packet los s and the average loop

time is 292 ms. This is a good performance for IP over PRIME in field conditions.

- The local SCADA is connected to the RTU through IP over PRIME. Although due to

configurability and addressing limitations of both the RTU and SCADA sys tem successful 104

traffic exchanges is not possible during the testing. Anyway, bidirectional 104 traffic is

18 This is a software tool developed by Iberdrola to perform RTU point -to-point tests monitoring different protocols traffic.



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exchanged and the concept is validated. The result is the same with a RTU simulated in a

second PC (WinPcPau test tool) so only 104 rejection traffic is exchanged.

- 104 traffic exchanges over IP over PLC PRIME are validated although further performance

measurements could not be taken in an operation environment.

4.2.4 USE CASE 2: SS WITHOUT REMOTE ACCESS - RESULTS, PERFORMANCE AND TOOLS

4.2.4.1 TEST SETUP AND CONDITIONS

The aim is to simulate SS locations where the SS does not have enough GPRS/3G coverage to let the

router establish a good connection with the AMI Head System. In this context GTP capabilities provide

an IP connection over PRIME network to an alternative location (such as a meter room nearby), from

which the GTP should be the one making the bridge to GPRS/3G connecting with the AMI Head System.

This scenario has been selected in order to test the capability, in terms of bandwidth, of IP over PRIME.

This would be the transmission medium for the information exchanged between the AMI Head System

and the AMI data concentrator in the SS. Figure 43 shows the network architecture in an SS representing

the test setup to be validated within the demonstrator. Originally, a 3G or GPRS router is the network

element responsible for connecting the AMI Head System with the AMI data concentrator. AMI data

concentrator is the Base Node in PRIME network, and there are only meters as PRIME Service Nodes.

This architecture offers an alternative Wide Area Network (WAN) access through a meter room offered

by the UPGRID GTP as described above.

FIGURE 43: ARCHITECTURE FOR USE CASE 2 SS WITHOUT REMOTE ACCESS DEPLOYMENT (CCT = DATA CONCENTRATOR,

GTP = PRIME GATEWAY, METER = SMART METER)



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FIGURE 44: USE CASE 2 TEST ENABLING WAN ACCESS FROM THE METER ROOM OF GERNIKAKO LORATEGIA 3

The IP traffic exchanged between AMI data concentrator and AMI Head System is:

- Hypertext Transfer Protocol (HTTP) traffic to access the AMI data concentrator web page. - HTTP traffic to transmit and receive Web Services.

If the SS does not have enough GPRS/3G coverage to let the router establish a good connection with the

AMI Head System, DSO would have to deploy an alternative transmission method (often expensive),

such as a proprietary optical fibre link. However, using the GTP capabilities to provide an IP connection

over PRIME network, DSOs can avoid the investment in other transmission methods.

Field testing requirement was one SS with a real or simulated coverage issues that would stop remote

communication. This SS should have a suitable meter room with enough space for an UPGRID portable

cabinet installation. Remote access to elements in the SS (any element such as remote control) would be

offered from the meter room. MIRIBILLA 6-BILBAO SS and its meter room Gernikako Lorategia 3 are

selected within UPGRID demonstrator area for this deployment.

A summary of the implemented measures required for the tests are presented next. Test plan and

execution is detailed in Annex III.

- Measure_1: Remote access to the AMI data concentrator from the meter room where the GTP

with WAN access is installed. This is IP over PRIME traffic.

- Measure_2: Remote access to the AMI data concentrator from the meter room where the GTP

with WAN access is installed while AMI reading data is exchanged. This means that IP over PRIME

traffic and AMI traffic are exchanged simultaneously.

- Measure_3: Remote access to the GTP with WAN access installed in the meter room from the

AMI operation system at Iberdrola premises. This ensures the last step of WAN remote

accessibility.

- Measure_4: Remote access to AMI data concentrator from the AMI operation system at

Iberdrola premises, being the first step the WAN connection to the GTP with WAN access



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installed in the meter room. This measurement is not possible due to routing limitations in

Iberdrola field operation networks.

4.2.4.2 TEST RESULTS AND PERFORMANCE

Based on the main measures to be taken, listed in the section above, and detailed in Annex III, this

section provides a summary of the test results and performance obtained from field testing.

- Remote access to the AMI data concentrator from the meter room where the GTP with WAN

access is installed is possible. Web server accesses are done using IP over PRIME channel and the

performance is slow but successful. This was the expected result so UPGRID concept is validated.

- ICMP packets are sent to the AMI data concentrator from the meter room where the GTP with

WAN access is installed. AMI reading data is exchanged in parallel, so IP over PRIME traffic and

AMI traffic are exchanged simultaneously. This latency test shows that access is possible

although there are some packets that do not arrive to the destiny (13% of the packets in this

scenario are lost). PLC PRIME channel sharing has an impact in the time performance of IP over

PRIME. From the measurements we take loop packet times from a minimum of 325 ms to a

maximum of 3.775 ms. Being the average 1.287 ms. This matches with the expected result,

simultaneity of traffic exchange over PLC PRIME is possible but bandwidth is limited so time

performance is affected.

- Finally, remote access to the GTP with WAN access installed in the meter room from the AMI

operation system at Iberdrola premises is validated. This ensures the last step of WAN remote

accessibility.

4.2.5 USE CASE 3: LV BACKUP FEEDER SMART-SWITCH APPLICATION - LIMITATION

FOUND IN THE DEMONSTRATOR AREA

This scenario has been analysed in order to test a remote control application to be applied for LV backup

feeder switching from one SS to an alternative one. It is referenced as LV backup feeder smart-switch

application. The approach followed here is to use remote control application (IP over PRIME) in order to

manage this feeder switching and therefore SS switching.

This is an alternative future solution that would be applicable in scenarios where mesh LV networks are

available. It requires SS with LV backup feeders where remote control for smart-switching is applicable.

This means that there should be LV points in the network where a second LV feeder from a backup SS

arrives. This kind of LV grid allows switching to a backup SS in case of supply faults or anomalies in its

main SS.

The application connects an IP smart-switch to a GTP device (with IP over PRIME enabled). Therefore

operates the smart-switch over IP over PRIME remotely and makes a LV backup feeder switch. Figure 45

shows the topology required in order to test this LV backup feeder smart-switch application.



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FIGURE 45: LV GRID TOPOLOGY WITH BACKUP FEEDER REQUIRED (FB = FUSE BOX, SS = SECONDARY SUBSTATION)

This LV smart-switch application requires the installation of UPGRID cabinets with GTP devices and IP

smart-switches in intermediate LV feeder points where two feeders from independent SS meet. This grid

topology condition is too specific and therefore it was difficult to deploy this scenario for testing in the

UPGRID Spanish demonstrator area.

FIGURE 46: LV GRID TOPOLOGY AVAILABLE IN THE DEMONSTRATOR AREA (FB = FUSE BOX, SS = SECONDARY SUBSTATION)

This alternative was presented and explained in [2]. However, all SSs analysed in the demonstrator area

have the structure shown in Figure 46, which is not compatible with the required architecture for testing

use case 3. This has been checked during field visits. For example, Figure 47 shows images taken during

a field visit to VALENTIN DE BERRIOTXOA SS where field deployment of this use case was discarded.

Therefore, although this is an interesting application for LV remote control over IP over PRIME it has not

been deployed and tested at field in the scope of UPGRID project.

FIGURE 47: FIELD VISITS TO VALENTIN DE BERRIOTXOA SS WHERE USE CASE 3 DEPLOYMENTS IN THE FIELD WAS

DISCARDED

SS SS FB FB

SS SS FB FB



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4.2.6 APPLICABILITY AND NEW OPPORTUNITIES

This section analyses how a multiservice PRIME subnetwork could be implemented today in field

operation. Short-and medium-term opportunities and benefits are identified as well. These concepts,

once validated, have a direct applicability.

- UPGRID actions that enable a multiservice PRIME network using IP over PRIME allow taking

advantage of the telecommunications infrastructure that is deployed for smart metering

purposes.

- Smart metering is the first application. Then actions are being done in order to support further

functionalities such as remote control in LV. These PLC networks provide a PLC-based

“coverage” area, linked to the LV grid that is able to support additional services and applications

apart from the feature of managing smart meters. Other smart grid related applications, such as

DER integration and electric vehicle (EV), may use the same telecommunications network as

well.

- IP over PRIME development done in order to support remote control over PLC is a standard and

interoperable initiative. PRIME PLC specification covers the multiservice premises it; minor extra

requirements identified are in standardization progress within the PRIME Alliance.

- Three applications (use cases) are analysed within UPGRID, demonstrating the two first. This

feasibility of remote control traffic using IP over PRIME is an opportunity to extend other

concepts.

- Application 1: PLC PRIME allows the transfer of control traffic for remote control applications

coexisting with metering applications. Communicate with an RTU, previously installed in a SS,

but now replacing the current transmission media (Ethernet) with PRIME. This means that the

RTU traffic (IEC 60870-5-104) is transported over PRIME instead of over Ethernet.

- Application 2: PLC PRIME allows the remote access to a SS without WAN coverage through a

meter room with WAN coverage. Extracting metering and control data of the SS though IP over

PRIME to another location where WAN access is possible.

This is applicable in situations where the SS does not have enough GPRS/3G coverage to let the

router establish a good connection with the AMI Head System. Here the DSO has to deploy an

alternative transmission method (often expensive), such as a proprietary optical fibre link.

However, using the GTP capabilities to provide an IP connection over PRIME network, DSOs can

avoid the investment in other transmission methods.

- Application 3: This remote control application can be applied for LV backup feeder switching

from one SS to an alternative one. It is referenced as LV backup feeder smart-switch application.

The approach followed here is to use remote control application (IP over PRIME) in order to

manage this feeder switching and therefore SS switching.

This is an alternative future approach that would be applicable in scenarios where mesh LV

networks are available. It requires SS with LV backup feeders where remote control for smart-

switching is applicable. This means that there should be LV points in the network where a

second LV feeder from a backup SS arrives. This kind of LV grid allows switching to a backup SS

in case of supply faults or anomalies in its main SS.



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4.3 MANAGEABLE PRIME SUBNETWORK (SNMP MONITORING):

EVALUATION AND CONCLUSIONS

The goal is to deploy a PRIME Management system (software solution) to monitor the basic

performance parameters of a PRIME subnetwork. This monitoring capability is the initial requirement to

integrate remote control over PRIME as described in 4.2. This section describes what this approach is

about, the benefit compared with previous solutions, tests performed and results of the field

deployment done within UPGRID project. The chapter ends with an analysis of the main benefits and its

applicability based on the results obtained. Annex IV and Annex V complement the tests with more

detailed data and information.

4.3.1 REQUIREMENTS FOR A MANAGEABLE PRIME SUBNETWORK

PLC PRIME subnetwork deployed for smart metering applications is a communication channel that

needs to be monitored. This is even more important for new applications integration in the multiservice

network concept introduced in the section above.

This PRIME subnetwork monitoring capability implies:

- Software (SW) evolution in the data concentrators deployed in the field. SNMP PRIME MIB has

been defined and implemented in incremental phases during the lifetime of demonstrator. This

network management functionality is implemented as a firmware version that can be installed

and validated in AMI data concentrators already deployed in UPGRID demonstrator area.

- A web tool or SW System (Network Management System) for collecting MIB was specified,

designed, constructed and tested. This web tool has been already installed in Iberdrola premises.

It is connected to the internal Base Nodes of AMI data concentrators and explores its data.

Therefore, the deployment tested in this section is based on the installation of a new firmware version,

in a set of field AMI data concentrators that supports SNMP PRIME MIB. All of these devices are

hardware devices in operation within the demonstrator area that required a SW evolution that was

designed and developed within the scope of UPGRID project. No field action is required for this

deployment as configuration and monitoring is done remotely (saving Field Crews movements). Figure

48 shows the architecture of this field deployment.



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FIGURE 48: FIELD SS MONITORED SNMP WEB TOOL (CCT = DATA CONCENTRATOR, IBD = IBERDROLA, FW = FIRMWARE, SS

= SECONDARY SUBSTATION)

4.3.2 FIELD VALIDATION CONDITIONS - RESULTS, PERFORMANCE AND TOOLS

The scope of the deployment has covered:

- 40 field AMI data concentrators are selected in the demonstrator area (i.e. Bilbao and

Baracaldo).

- This covers 14.000 smart meters (this is the number of Consumers in the demonstrator area that

can benefit from the advanced data analysis that SNMP monitoring offers ).

- UPGRID SNMP PRIME MIB is installed and enabled AMI data concentrators.

- AMI data concentrators are integrated for data collection from the UPGRID web tool

development.

- No field visit required: configuration and monitoring is remotely done.

Based on the specification described in [2], a software evolution is implemented for ZIV PRIME data

concentrators. The internal Base Nodes of these devices are able to offer the required information so

PRIME subnetwork can be monitored. For this use of case, following MIB parameters have been

recovered:

Number of Terminals19 in the subnetwork -> OID: 1.3.6.1.4.1.15732.23.1.2.0 – Unsigned 32

Number of Switches in the subnetwork -> OID: 1.3.6.1.4.1.15732.23.1.3.0 – Unsigned 32

19 Terminals and Switches are status defined in the PRIME specification.



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As said before, in the UPGRID demonstrator, this tool has monitored 40 devices, all of them installed in

field and accessible from the Iberdrola office. Next are the steps that had been followed to gather data

from the Base Nodes:

- First of all field data concentrators are upgraded and configured in order to enable their PRIME

advanced SNMP monitoring capabilities.

- Then, it was necessary to provision the 40 Base Nodes in the tool (see Figure 49 and Figure 50).

FIGURE 49: SCREENSHOT OF THE SNMP WEB TOOL PROVISIONING INTERFACE

FIGURE 50: SCREENSHOT OF THE SNMP WEB TOOL PROVISIONING INTERFACE II

- After that, the available operations as scheduling tasks/actions have been configured. In the task

scheduler the user is allowed to configure both, how often an operation should be applied and

which smart meters are to be accessed for a specific task. In this case, the periodicity of the

recollection is 5 minutes and the smart meters where all of the 40 Base Nodes (see Figure 51).



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FIGURE 51: SCREENSHOT OF THE SNMP WEB TOOL SCHEDULER INTERFACE

- Once the task is configured, it is possible to find information about the provisioned Base Node.

Two tasks are needed, one for the number of Terminals in the network and the other for the

Switches, both tasks are shown in the image below (see Figure 52).

FIGURE 52: SCREENSHOT SHOWING ADDED TASKS

- Figure 53 is a real example from a data concentrator in the demonstrator area. The number of

PRIME registered nodes (smart meters) – green in the figure - and the number of nodes acting as

repeaters – blue in the figure – are represented. These curves are directly offered from the

SNMP web tool, ensuring its usability.



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FIGURE 53: SCREENSHOT OF RECOLLECTED DATA FROM A REAL DATA CONCENTRATOR. NUMBER OF TERMINALS (IN

GREEN). NUMBER OF SWITCHES (IN BLUE)

All the results from the test are available in Annex IV. The test had been done in 40 data concentrator

during 4 days. Since the data concentrators are installed in field, the access is made via firewall. This

firewall is opened 12 hours and then it has to be re-logged. Because of that, some data is lost and not

shown in the graphics. With collected data it is possible to notice issues in the network such as locations

where there is a high level of noise that blocks the signal (SNR or signal to noise disturbances). This

example is shown in Figure 54 . It is possible to observe how, at certain times, the number of Terminals

(green line) and Switches (blue line) is zero (i.e. both lines fall to zero). This will be the time slot where

the noise is louder.

FIGURE 54: SCREENSHOT OF RECOLLECTED DATA FROM A REAL DATA CONCENTRATOR WITH NOISE ISSUES. NUMBER OF

TERMINALS (IN GREEN). NUMBER OF SWITCHES (IN BLUE)



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Besides the information provided above, Annex V describes in detail all the steps for data collection for

a particular example. The SS chosen for this example is located inside the demonstrator area, in Bilbao,

and it provides service to 220 Consumers.

4.3.3 TEST RESULTS AND PERFORMANCE

The performance results obtained from the SNMP monitoring deployment and analysis done in the

UPGRID Spanish demonstrator are as follows:

- The aim was to propose a SNMP based Network Management System (NMS), and the initial

steps for a prototype implementation over a massive PLC PRIME deployment. This goal is

successfully achieved within UPGRID project.

- In the case of the SNMP based tool, SNMP web tool specification and development has been

successful. SNMP MIB integrated into the AMI data concentrators is accessible from the SNMP

web tool system. This has been validated both in laboratory and in the field (demonstrator area).

Each AMI data concentrator has an internal PRIME base node that manages the network. This

analysis tool makes use of the data provided by the PRIME base nodes and enables a

manageable PLC PRIME network.

- The tool has monitored a significant number of devices of the demonstrator area (about 40),

and, at this stage, with the implementation done, PRIME monitoring is ensured.

- Also, regular AMI operation is improved; monitoring allows detecting real time issues. AMI

deployments monitoring is improved. AMI data concentrator performance information is

available now and included in the SNMP web tool developed for UPGRID project.

- Based on the results and future deployments scheduled, further evolution of the tool would be

done in the coming years (outside the scope of UPGRID project). Note that in the results graphics

shown (Figure 54 and Annex IV) only two of the SNMP objects (i.e. number of Terminals and

Switches) are really stored and represented by the SNMP web tool. This monitoring already

improves the manageability and knowledge of the network. But note that the complete

specification designed within the scope of UPGRID project covers tens of objects that will need

to be integrated in this SNMP web tool in the coming months and years.

4.3.4 APPLICABILITY AND NEW OPPORTUNITIES

This section analyses how a manageable PRIME subnetwork through the SNMP system described could

be implemented today in the field operation. Short-and medium-term opportunities are identified as

well. Then, enabling a manageable PRIME subnetwork has the following applicability and benefits:

- The deployment of SNMP based NMS over PLC PRIME networks allows PRIME network

monitoring and remote management.

- The PRIME subnetwork monitoring capabilities that were designed, developed and deployed

within the UPGRID Spanish demonstrator imply several benefits for the DSO and for the final

Consumer, as indicated in the following points.

- This PRIME monitoring is the first step that enables a PRIME multiservice network. This is a key

enabler for the control traffic exchange over PLC PRIME developed also in the scope of UPGRID



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demonstrator area. PRIME network knowledge helps designing the best approach in order to

introduce LV remote control in addition of AMI regular operation.

- DSOs will benefit as they make the most of the investment done for AMI deployments. These

AMI deployments can be used now for further applications, not only for billing purposes. These

applications are mainly focused on network operation optimization and remote control

capabilities over LV grid.

- PRIME communication channel usage characterization is obtained: The AMI evolution requires a

better knowledge of the communication channel enabled over the LV line with PLC PRIME. SNMP

monitoring offers this information required of PRIME PLC channel and bandwidth usage.

- Moreover, the regular AMI operation is improved, as monitoring allows detecting real time

issues namely:

o AMI deployments monitoring is improved. AMI data concentrator performance

information is available now and included in the SNMP web tool developed for

UPGRID project. This allows the DSO to detect in real time issues and anomalies in the

AMI data concentrators developed in the field.

o In case of faults or anomalies, the evolution of these applications would, in medium

term, reduce the faults clearing time and therefore increase the quality of service

offered by the DSO to Consumers. Note that these anomalies would be mainly related

with LV incidents that would mean that groups of smart meters would be powered-off

and therefore disconnected from the PRIME subnetwork. AMI data concentrators

with this SNMP monitoring functionality enabled will be able to realise those sudden

variations in Number of Terminals in the subnetwork. This information will be

available in the SNMP web tool at the system side.

o Note that this data, once available at the system, could be integrated and correlated

with other events and data already being processed at the DSOs system. Applying

data analytics and correlation of this information, with the geographical location of

those smart meters disconnected, could help locating areas with a high probability of

being affected by a LV incident. Note that this would be realised in the very moment

the fault is occurring, so fault management systems could have valuable information

that would improve their operation. Of course this requires further evolution in the

systems and in many elements to be integrated, but of course these are applications

to be studied and developed in the coming years.

o All this comes with a low cost, as this monitoring is enabled with a SW evolution of

the AMI data concentrators already installed in the field. SNMP web tool for data

correlation is also required.

- Then, the monitoring and information for the DSO will impact directly in a better management of

incidents, having a direct impact into the final Consumer.



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4.4 CONCLUSIONS ABOUT PRIME BASED FUNCTIONALITIES

UPGRID Spanish demonstrator contributions improve PRIME subnetwork capabilities. Solutions

validated in the demonstrator have a direct impact into the DSO operation and final Consumer.

The aim has been mainly to take advantage of the telecommunications infrastructure that is deployed

for smart metering purposes offering further information and services that increase its value and

usability. Developments have been done in order to validate these functionalities (e.g. LV remote

control can be enabled over existing AMI deployments).

A multiservice PRIME subnetwork can be enabled, as demonstrated during the deployment and testing

phase. The conclusions of this characterization determine that IP over PRIME is a feasible alternative to

transport RTU control traffic using PLC PRIME as channel.

- Tests plans and measures have been focused on the feasibility of IP transport over PLC-based

Smart Metering networks.

- The aim was to demonstrate the feasibility of IP transport for remote control applications and

the extra-bandwidth of newly deployed PLC-based networks for smart metering. And this has

been achieved.

- The impact on latency due to sharing PRIME channel between AMI data and IP data is

acceptable, so both types of traffic (control and metering) can coexist in a PRIME network.

- Three applications have been analysed within UPGRID; demonstrating two of them. This

feasibility of remote control traffic using IP over PRIME is an opportunity to extend other

concepts.

- PLC PRIME allows the transfer of control traffic for remote control applications coexisting with

metering applications. This was the first use case validated.

- PLC PRIME allows the remote access to a SS without WAN coverage through a meter room with

WAN coverage. Extracting metering and control data of the SS though IP over PRIME to another

location where WAN access is possible. Using the GTP capabilities to provide an IP connection

over PRIME network, DSOs can avoid the investment in other transmission methods. This was

the second use case validated.

This multiservice subnetwork requires a higher level of monitoring and knowledge of the PLC channel.

This is a key element in order to be able to measure the impact of PRIME channel usage in each

situation. Therefore, a manageable PRIME subnetwork deploying SNMP based NMS is designed,

specified, developed and validated within UPGRID project.

- PRIME network monitoring and remote management is improved thanks to this SNMP protocol

deployment.

- This PRIME monitoring is the first step that enables a PRIME multiservice network. This is a key

enabler then for the control traffic exchange over PLC PRIME developed also in the scope of

UPGRID demonstrator area.



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- The aim was to propose a SNMP based NMS, and the initial steps for a prototype

implementation over a massive PLC PRIME deployment. This goal is successfully achieved within

UPGRID project.

- It implied a software evolution in the AMI data concentrators deployed in the field. So their

internal PRIME Base Node is able to gather and registered advanced PRIME PLC monitoring

information.

- It also required the development of an SNMP web tool, to be integrated at a system level

(Iberdrola’s premises). This tool gathers information from AMI data concentrators and

graphically shows their PLC PRIME network stability and performance.

- The development and integration of these elements has been validated both in laboratory and in

the field (demonstrator area). At this stage, with the implementation done, PRIME monitoring is

ensured.

- Also, field deployment confirms that regular AMI operation is improved; monitoring allows

detecting real time issues.



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5. LV NETWORK OBSERVATION AND MAINTENANCE BASED

ON SMART METER EVENT PROCESSING AND ANALYSIS

The main objective of this chapter is to report on the improvements and opportunities that the smart

meter event processing and analysis performed in the Spanish demonstrator brings with regards to LV

network observation and maintenance. First, the introduction provides an overview of the work done in

the demonstrator (further details can be found in [1]); while the second section presents practical

results and conclusions.

5.1 INTRODUCTION

The analysis aims to identify the potential of processing smart meter events to enhance the LV network

maintenance. From a practical point of view, smart meter events provide useful alerts and notifications

about anomalous network situations. Smart meter events cover circumstances related to QoS, demand

response, security failures, fraud, communications and specific issues of network devices. They are

classified in a broad range of more than 150 types [17]. In addition to this classification, events are

prioritised as spontaneous or non-spontaneous. The first ones are reported to the AMI Head System

when the event takes place. By contrast, the second ones are stored in the smart meters until there is a

request (e.g. once per week) from the AMI Head System to retrieve them.

The offline smart meter event analysis within the AMI architecture in the UPGRID demonstrator is

shown at Figure 55. The data concentrator acts as gateway to smart meter data at SS level, being able to

communicate with the DSO Meter Data Management System (MDMS) through different type of

communications. The MDMS holds and processes smart meter data. Within this framework, smart

meter events are retrieved to be analysed offline. It is important to note, as indicated in Chapter 3, that

the LV NMS also handles (online) some smart meters events as alarms or incidents.

FIGURE 55: OFFLINE SMART METER EVENT ANALYSIS WITHIN AMI ARCHITECTURE



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An initial study showed that 700.000 smart meter events are recorded per day (in average) in the

Vizcaya area (Figure 8). Then a set of strategies has been undertaken in the demonstrator to face the

analysis of this huge quantity of information in a semi-automated way as follows:

Developing tools based on Visual Basic for Applications (VBA) to automate event gathering,

filtering and sorting processes, strengthening the accuracy and repeatability of the analysis.

Focusing the study on: specific event types, most convenience timeframe for running the tools

and data aggregation at network asset level.

Improving the detection of hot spots at distribution network taking into account other field

measurements, for instance from supervisory meters installed in each SS.

Due to the early stage of leveraging smart meter events as key data for network maintenance, the

analysis performed has been conceived as an iterative and flexible process, as can be seen at Figure 56.

For this reason it was decided to use the VBA as an easy way to adapt development environment to

deploy and test different approaches. Then, based on that, the analysis has been focused in assessing

the convenience of such a tool for the expected usability and in identifying functionalities for a short-

medium term final tool.

FIGURE 56: EVENTS ANALYSIS FLOW CHART

5.2 EVALUATION AND CONCLUSION

5.2.1 MOST CONVENIENT TYPE OF SMART METER EVENTS FOR ENHANCING LV

MAINTENANCE AND OTHER PRACTICAL PROCEDURE DETAILS

Due to the vast number of events that smart meters report to the MDMS, it was decided to start the

analysis performing a pre-selection of some of them to have a manageable quantity. The first approach,

based on matching residential end-users claims regarding voltage quality with smart meter events



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(reported along 2015 in the areas of Vizcaya, Burgos, Castellón and Madrid20), was proved not to be

useful. This fact leads to the following conclusions:

There is misleading information due to the crucial role of human factor at claims reporting. In

some cases the date of the claim is far away from the date of the reported incident. In other

cases the electrical knowledge of end-users is focused mainly on outages, even scheduled ones.

Most of incidents are related to power interruption, even due to AMI roll out scheduled

interruptions, and these do not give any clues to improve distribution.

Event recording can be improved. For example, smart meters from different manufacturers

record sometimes disparate events during the same incident, some events are not recorded in

the MDMS because there are meters which are not recording any event since certain date, and

in other cases only certain events seems missing.

Thus, it was concluded that another approach was needed. The second attend, that ultimately proved to

be valid, was based on the Iberdrola experience on the distribution network. As explained, the flexible

approach followed in this analysis (Figure 56) has allowed adding any type of event that was believed

useful. Therefore, the selection of smart meter events shown in Table 13 has been proved convenient

for additional LV maintenance enhancements based on the tests performed in the demonstrator which

are presented in the next sections.

TABLE 13: TYPE OF SMART METER EVENTS FOR LV NETWORK MAINTENANCE ENHANCEMENT

Type Group Event Id. Description

Closed quality incidents

3 13 Average voltage between phases is under lower l imit

3 14 Phase 1 voltage is under lower l imit



3 17 Average voltage between phases is over upper l imit

3 18 Phase 1 voltage is over upper l imit



3 22 Long term outage detected at phase 1

Standard

1 1 Meter restart event with missed data

1 2 Meter restart event without missed data

1 3 Supply failure at meter event

1 7 Loss of neutral

5.2.2 SELECTION OF MAIN ANALYSIS FUNCTIONALITIES

Based on the event selection (see Table 13) and the test results shown in next sections a series of

functionalities have been proved as the most useful ones for the expected proposes. A part from

investigating the applicability of offline smart meters events analysis on enhancing LV network

20 Other areas, apart from the demonstration one, have been included in the study for having a bigger variety of data.



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maintenance, the demonstrator has investigated which would be the most convenient and useful

requirements to be included in a near-future tool that would be integrated within the current MDMS.

The main analysis functionalities selected in the demonstrator are presented in Table 14.

TABLE 14: MAIN ANALYSIS TOOL DEVELOPED IN THE DEMONSTRATOR FOR EVENT ANALYSIS

Tool Objective

Search for outage missed events Calculates the percentage of missed events when a specific outage incident

takes place.

Get time out of voltage limits of each SS Calculates the time that each SS is out of voltage limits based on the duration of

the undervoltage/overvoltage events registered by the smart meters associated

to that SS during the defined analysis time period.

Get time out of voltage limits of each FB Calculates the time that each FB is out of voltage limits based on the duration of

the undervoltage/overvoltage events registered by the smart meters associated

to that FB during the defined analysis time period.

Get supervision meter reports Calculates the percentage of hourly voltage measurements that are out of

voltage limits.

Additional practical conclusions have been drawn during the first tool tests:

In spite of the event type selection, the analysis of “loss of neutral” event showed that there was

a considerable quantity of false positives. These events belong to smart meters without neutral

connection due to meters installation issues, even though the power supply and the billing are

correct. For this reason, they are excluded at this stage.

For example, the analysis of events collected in November 2015 pointed out that a single SS

held the majority of them (86 events). What is more, all of them belonged to the same smart

meter. However, voltages measurements at that meter were within the regulatory voltage

limits21. For this reason, “loss of neutral” events were excluded for coming analysis.

It is concluded that a week period is the best time frame to launch the developed macros to

optimise the execution time. Longer periods would be useful for the analysis point of view since

more events can be added by elements (e.g. FB and SS), but the execution of database queries

take much more time, as well as sometimes the number of events exceeds the maximum

number of rows at Excel sheet.

Regarding the aggregation level, higher than the smart meter has revealed as a good approach.

This means grouping the analysed smart meter events at their connectivity elements, such as FB

or SS. In this way, LV network weaknesses are easier to detect, while grouping events makes the

quantity of analysed data more manageable at the same time.

21 There are two types of connections in the studied regions, on basis of the nominal voltage. B01: supplying 133V, with regulatory voltage limits between 123V and 142V (remaining old LV network). B02: supplying 231V, regulatory voltage limits between 215V and 247V.



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5.2.3 DETECTION OF MISSED EVENTS

This analysis is aimed at quantifying outage missed events and then, get an order of magnitude on this.

That is, smart meters that do not send the expected events when they should have. To perform the

study, one of the developed VBA macro has been used when it was known that LV incidents affected all

smart meters connected to certain SSs. After these kinds of incidents, the following events should be

recorded at the MDMS:

Supply failure at meter event.

Meter restart event without missed data or meter restart event with missed data.

Long term outage detected at phase 1. In order to make easier the analysis, only the outage

events at phase 1 are considered, to analyse in the same way the three-phase and monophasic

meters.

Then, an index is obtained for each element: smart meter, FB and SS. The index is calculated in terms of

the missing events after the incidents, as an average of recorded events. This way the closer the index is

to 0, the more events are missed, while the index is 1 if there are not missed events. In addition to this,

some extra information is included, for instance the smart meter read rates. Moreover, a colour code is

used for showing the calculated indexes based on three value intervals.

TABLE 15: EXAMPLE OF GRAPHICAL PRESENTATION OF RESULTS AFTER EXECUTING THE MACRO TOOL (LEFT). SUMMARY

OF RESULTS OBTAINED AFTER A SUITABLE INCIDENT HAPPENED ON 12/02/2016 THAT AFFECTED 14 SSS (RIGHT).

SS_id

nº of smart

meters

Total nº of searched

events received

Index (% of

events received)

1 269 635 0,79

2 390 1069 0,91

3 208 634 1,02

4 339 859 0,72

5 285 761 0,89

6 107 321 1

7 327 74 0,08

8 257 528 0,68

9 97 324 1,11*

10 230 263 0,38

11 358 783 0,73

12 325 683 0,7

13 264 496 0,63

14 9 12 0,44

Average index value 0,72

*Being higher than 1 means that there are smart meters registering the situation (the supply

shortage) more than once during the incident. Since the index is higher than 1 it implies that

there are not missing events what was the purpose of the test.

The conclusion after several incidents analysis is that around the 30% of events are missed. This

percentage could be extrapolated to the total number of events recorded at MDMS. The main reason is



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that the majority of the smart events are non-spontaneous, and they are gathered weekly into the

MDMS, during a certain time-slot. When this time slot ends, those smart meter events which have not

been sent are not recorded.

As a result, it is inferred that a new smart meter firmware configuration would be needed in order to

discard some events, such as communication events, useful during the AMI roll out, but dispensable

when the AMI deployment in an area is consolidated. Another alternative to investigate would be to

propose an event masking mechanism. Most of the smart meters have the capability to define (via

bitmask transported over COSEM object) which event should be logged and which events should be

spontaneously sent (notified) to the data concentrator and AMI Head System. This is more flexible than

events hardcoded in firmware, with no option for masking/unmasking.

Effectively, the amount of events to be retrieved from the smart meters would be reduced, theoretically

avoiding, or at least reducing, the number of missed events that are more useful for LV maintenance.

5.2.4 FIELD APPLICABILITY OF SMART METER EVENT ANALYSIS OUTCOMES

This study has been aimed at testing the truthfulness of transferring the event analysis results to field.

Although the core analysis has been done for Vizcaya (Figure 8) where the demonstration area is

included, three other locations have been added to the study (i.e. Burgos, Castellón and Madrid) with

the aim of covering different climates, rural and urban distribution network areas and including a variety

of Consumers. This has been also done as replicability concepts prove.

The macro tools are used over the set of smart meter events registered in Vizcaya between January

2016 and October 2016 to identify those FBs with worst undervoltage and overvoltages behaviour

(based on the time that their smart meters are out of voltage limits). Table 2 and Table 3 showed these

cases for further exploration (see section 5.2.5). A compromise criterion among the number of weeks

recording undervoltage / overvoltage events, the number of meters recording events and the

percentage of time out of voltage has been selected.

TABLE 16: WORST CASES OF UNDERVOLTAGE EVENTS (AT FB BASE) DETECTED IN THE VIZCAYA AREA

SS_id FB_id %time Out of V

(Average)

Maximum %time

out of V

Number of Meters

(Average)

Number of

weeks

SS_1 FB_1 12% 25% 9,82 44

FB_2 13% 29% 2,85 40

SS_2 FB_3 1% 42% 8,93 43

SS_3 FB_4 12% 29% 8,75 44

SS_4

FB_5 12% 36% 4 40

FB_6 11% 28% 3,98 43

SS_5

FB_7 24% 72% 1,91 44

FB_8 24% 44% 1 44

FB_9 23% 46% 2 44

FB_10 19% 48% 1 43



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TABLE 17: WORST CASES OF OVERVOLTAGE EVENTS (AT FB BASE) DETECTED IN THE VIZCAYA AREA

SS_id FB_id %time Out of V

(Average)

Maximum %time

out of V

Number of

Meters(Average)

Number of

weeks

SS_6 FB_11 12% 25% 9,82 44

FB_12 13% 29% 2,85 40

SS_7 FB_13 1% 42% 8,93 43

SS_8 FB_14 12% 29% 8,75 44

SS_9 FB_15 12% 36% 4 40

This information has been transferred to the maintenance responsible of the demonstrator area in

order to study it in detail and then determining if a field work is required for improving some of the

cases identified. Unfortunately, at the moment of writing this deliverable, this study is still undergoing.

Fortunately, additionally to the Vizcaya analysis, undervoltage and overvoltage smart meter event

processing have been performed in other zones and the potential cases for improvement delivered to

maintenance staff of these areas. They have provided positive feedback about the usability of the

results obtained from this analysis. It is worth mentioning that the involvement and proactive behaviour

maintenance responsible is of great importance to make the most form this kind of information. Some

examples are shown next:

In Castellón (December 2015 data) after the field analysis of the 5 worst overvoltage cases

detected (similar to those presented in Table 16 and Table 17), it was verified that there was a

one-to-one relationship in 100% of cases regarding the distance between the FBs and SSs, and

the time being over the voltage limits (calculated through smart meter events). One of the cases

is presented in Figure 57. The FB with code 984847 is the nearest to the SS (5010000233) and it

is the one being more time over the regulatory voltage limit. By contrast, the FB with code

989160 is the one with fewer events and it is the farthest from the SS.

FIGURE 57: FIELD ANALYSIS OF OVERVOLTAGE EVENTS



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Concerning to undervoltage events, the 17 worst cases were considered within a field analysis as

well. The conclusion is that there is a one-to-one relationship in 80% of cases (15/17) between

the distance to SSs and time FBs are registering smart meters under voltage limits. The two

remained cases were related to connection issues: one for being fed from other FB and the other

because the characteristics of the cable were different (lower section).

It is worth mentioned that on April 2016, some days after registering events, there was a

Consumer claim from due to a breakage of neutral wire. Perhaps, this situation could have been

avoided if the out of voltage events would have been taken into account. Then, the consolidation

of the methodology proposed could be used to perform predictive maintenance and acting in

advance.

In Burgos, for one LV feeder with some FBs registering severe undervoltage episode in one week

(04/01/2016) some corrective measures are analysed, for example change the transformer tap

changer position or, alternatively, change the voltage connection to B02 (nominal voltage 231 V)

and/or change the type of cable in the last stretch of the feeder.

In other cases, no reasons have been found to implement field works after evaluating the event

analysis outcomes.

5.2.5 DETAILED ANALYSIS OF VOLTAGE MAGNITUDES ISSUES AT SUPPLY POINTS:

VIRTUAL REGISTER

Based on the demonstrator effort of analysing in detail those overvoltage and undervoltage cases

identified after executing the macro tools, it was concluded the necessity of checking voltage at

Consumer smart meters in near-real time in more detail to discard “fault positives”. As the majority of

smart meter events are non-spontaneous, they are analysed in hindsight, since they happened some

time ago. This issue hampers the event analysis, the timing replicability of scenarios, and then the

applicability of results at field. In this context, the Virtual Register (software based) functionality

(software based) has been developed and integrated in the MDMS, see Figure 58. It automatised the

process of polling voltages and currents measurements of the selected smart meter22 each 5 minutes

during 48 hours. This way the virtual register increases the supervision of LV grid, providing with real

measurements from suspicious meters in a remote way without the need of installing any temporal

devices at the Consumer premises.

The tool validation results show that from 361 smart meters over which the Virtual Register were

launched, in 90% of the cases there were enough measurements (>90%) to consider the set of data

representative for extracting conclusions.

22 It is worth mentioning that even though smart meters installed at field are able to register voltages and currents, Iberdrola is not sending them (at the present time) to the AMI Head System automatically once per day as happened with other measurements. However, they can be retrieved on demand when the operator requests them.



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Suspicious FBs included in Table 16 and Table 17 have been taken as the basis for testing this new

application. Then, voltage measurements of their smart meters have been gathered using the Virtual

Register.

FIGURE 58: VOLTAGE CURVE ELABORATED BY THE VIRTUAL REGISTER FOR A PARTICULAR SUPPLY POINT (SMART METER)

AND SHOWN THROUGH THE TOOL GUI

The results of this data collection are included in Annex VII. This information should be used by

maintenance responsible to decide if some field work (e.g. change the distribution transformer tap

changer position and change the cable in some section of the LV feeder) is required to improve the

voltage profile. At the moment of writing this deliverable and having provided the demonstrator area

maintenance responsible with this information, no field works have been performed yet.

By way of example, the information of the first SS (SS_1) at Table 16 is included next. There are 2 FBs in

the SS_1, which is within the worst undervoltage cases:

FB_1, with 11 smart meters.


The code of smart meters belonging to each FB is shown in Table 18, while the graphical representation

obtained with the Virtual Register for the six first smart meters on that table are included in Figure 59. It

is shown that all these smart meters have several measurements under the regulatory voltage (i.e.

measurements are below the red line indicated in the plots that indicates the regulatory voltage limit).

The other smart meters graphs are represented in Annex VII.

TABLE 18: SS_1 - METERS FROM WORST FB UNDERVOLTAGE

SS_NAME FB_CODE METER CODE

SS_1 FB_1 ZIV********44

SS_1 FB_1 ZIV********45

SS_1 FB_1 ZIV********49

SS_1 FB_1 ZIV********50 SS_1 FB_1 ZIV********51

SS_1 FB_1 ZIV********52

SS_1 FB_1 ZIV********53

SS_1 FB_1 ZIV********25

SS_1 FB_1 ZIV********27



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SS_1 FB_1 ZIV********51

SS_1 FB_1 ZIV********22

SS_1 FB_2 ZIV********34

SS_1 FB_2 ZIV********36

SS_1 FB_2 ZIV********37

FIGURE 59: MEASUREMENTS FROM FB_1 (PART 1)

Based on the experience gained on the use of this tool so far, it would be advisable to limit the number

of Virtual Register processes that are executed simultaneously on the same SS to avoid stressing the

communication network. In some cases it has been observed that all 5’ measurements were not

retrieved. This number has not been fixed yet. Some other features have been implemented after the

tests. For example:



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A watchdog to avoid initiates a Virtual Register process on a smart meter if there is already one

active process running on it.

The Virtual Register cannot be launched for a smart meter with a not successfully reading rate in

the last month. The measurements retrieved in this case would be mostly incomplete.

5.2.6 SUPERVISION METERS MEASUREMENTS TO COMPLEMENT THE EVENT ANALYSIS

Complementary to the use of smart meter events, hourly voltage measurements from distribution

transformer supervision meters (hereinafter supervision meters) installed in each SS (Figure 10) have

been proved useful in the analysis as well based on the demonstrator experience. For example, it

improves the detection of LV network hot spots at SS level since an anomalous voltage measurement

(out of limits) would determine that the cause is located at a LV feeder head instead of somewhere

downstream.

Moreover, thanks to the validity prove obtained in the demonstrator analysing supervision meter

voltage measurements, a similar functionality has being developed to automatically create reports on

these measurements (i.e. voltage, current and average powers). Then, maintenance responsible can get

information about the % of measurements within certain intervals per phase. This can motivate the

change of distribution transformers if the report shows voltage issues during a significant period of time.

5.2.7 REFINEMENT OF SUPERVISION METERS INVENTORY: INCONSISTENCIES DETECTION

As pointed out in section 5.2.7, it is possible to analyse the percentage of hourly supervision meter

measurements out of regulatory limits (overvoltage and undervoltage) executing one of the macro tools

developed in the demonstrator. This study was performed for May 2016 for Vizcaya area. It was

observed that the vast amount (96%) of supervisory meters have not any voltage issues, but it was

identified that there were some with the 100% of measurements out of voltage limits (Figure 60 shows

graphically the overvoltage analysis result). Thanks to this outcome and a subsequent detailed

investigation, an unexpected improvement was detected. That is, the identification of wrong labelled

supervision meters in the inventory data base. Some were labelled as B0123 when in reality it should be

B02 (reporting overvoltage) and vice versa (reporting undervoltage). Figure 61 shows 5 supervision

meters that register a voltage corresponding to B02 in phase 1 while they have been inventoried as B01

(the same happens with the other two phases even they are not shown).

23 There are two types of connections in the studied regions, on basis of the nominal voltage. B01: supplying 133V, with regulatory voltage limits between 123V and 142V (remaining old LV network). B02: supplying 231V, regulatory voltage limits between 215V and 247V.



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FIGURE 60: OVERVOLTAGE REPORT RESULTS AT SUPERVISORY METER

FIGURE 61: EXTRACT OF THE RESULTS OBTAINED AFTER EXECUTING THE VBA MACRO TOOL

Taken advantage of this finding, and in order to solve the issues in the complete data base, the same

study were performed for all the supervision meters installed in the Iberdrola network (Spain). As result,

418 out of 75.320 cases were identified as potentially wrongly labelled, Table 19. This information has

been transfer to the maintenance responsible of each Territorial Distribution Unit (TDU) to implement

the corresponding corrective actions that involve field visits to verify each case. At the end of February

2016 the number of cases was reduced up to 105 (75%).

TABLE 19: NUMBER OF SUPERVISION METERS POTENTIAL WRONG LABELLED

Geographical location (provinces)

Supervisory meters potentially wrong labelled

Location_1 59

Location_2 21 Location_3 2



Location_8 30





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Geographical location (provinces)

Supervisory meters potentially wrong labelled

Location_13 32



TOTAL 418

5.2.8 CONVENIENCE OF INTERACTIVE RESULT REPRESENTATION

The software tool Tableau Desktop [18] has been introduced to visualise results in an interactive way.

Therefore, the analysis is enhanced with a wide range of graphical features helping locate suspicious

spots (e.g. network areas with higher number of smart meters with undervoltages or overvoltages

issues) at the LV distribution network. Based on the evaluation, it has been concluded that this is a

useful functionality that help in the result interpretation and it is a mean for easier location of

investigated network issues. The main reason is that these kinds of analyses normally cover several

months to have a representative data sample. Then, the use of a graphical representation tool makes

easier drawing meaningful, consistent and practical conclusions. This tool allows aggregating data from

several sheets (generated by the demonstrator VBA macro tools) where, for example, each of them

contains weekly data from the elements, FB or SS.

For example, the number of undervoltage events per week in the Vizcaya region is represented in form

of bar chart, interactive map and table (Figure 62, Figure 63 and Figure 64). Presenting the information

in these modes facilitates the detection of, for instance, those weeks with highest ratios of voltage

issues and its network location:

It can be seen that there are some weeks which are over the average of events with erroneous

dates, such the 8th of August and 24th of October, with 46 and 88 undervoltage events

respectively.

It is also remarkable that the number of events over the maximum time (6 hours) is very

variable, but it is under the 5% of the total number of events.

The filter selected in Figure 63, helps to visualise FBs which smart meters have registered

undervoltage events on at least 40 out of the 44 weeks and with more than the 10% of the week

minutes under the voltage limit. Similarly, Figure 64, present the information on a table format.



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FIGURE 62: BAR CHART [NUMBER OF UNDERVOLTAGE EVENTS PER WEEK IN VIZCAYA (2016) ON BASIS OF ITS DURATION]

FIGURE 63: MAP [NUMBER OF UNDERVOLTAGE EVENTS PER WEEK IN VIZCAYA (2016) ON BASIS OF ITS DURATION]



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FIGURE 64: TABLE [NUMBER OF UNDERVOLTAGE EVENTS PER WEEK IN VIZCAYA (2016) ON BASIS OF ITS DURATION]

5.3 OPPORTUNITIES

Based on the experience gathered on the demonstrator, a series of next steps are identified to continue

developing the presented methodology on smart meter event processing:

Guarantee the standardization of event generation and sending commands at Consumer meters.

Reducing the percentage of missed events to ensure the reliability of events analysis.

Refinement of event processing, according to field performance, to avoid recording false positive

events.

Deep review of events priority to classify them as spontaneous, non-spontaneous or even as

non-recording at MDMS.

An analysis with even broader time horizon in order to eliminate temporalities or to avoid

misunderstanding consumption patterns.

Development of new tools to process the events, overcoming technical limitations of VBA

(execution time, maximum number of sheet lines, etc.).

Moreover, the development of the Virtual Register offers real measurements from specific

costumer meters, which could be very useful to distribution management issues.



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6. CONSUMER EMPOWERMENT TOOL

6.1 INTRODUCTION

A web-based computer tool for managing energy consumption rationally by Consumers has been

developed in the demonstrator.

This work exploits one of the UPGRID Function Objective selected and described in [4], “New

approaches for market design” and, more specifically, UPGRID sub-functionality “Web portal for

increasing the awareness of Consumers in order to leverage their participation in electricity markets”. It

is worth mentioning that smart meter measurements are the main source of data. Then, “Smart

metering data utilization” Function Objective is also relevant since it lays down the basis for the tool.

The UPGRID Spanish demonstrator has enhanced the previous tool version developed in the Bidelek

Sareak project. It has extended the tool scope being the main functionalities the following ones:

Presents structured information on users’ energy consumption (appliances, electricity

consumption, etc.).

Offers Consumers challenges to help reduce their energy consumption (energy saving by

appliance type).

Compares their energy consumption to that of an efficient Consumer.

Helps reduce electricity costs through knowledge of the following day’s electricity price.

In short, the aim of the tool is to ensure that Consumers have enough technically and economically

reliable information to allow them to take responsible decisions to help reduce their electricity

consumption.

6.2 EVALUATION

The following section summaries the results of the tool performance evaluation. The tool capabilities

are described in detailed in [3].

6.2.1 METERING DATA GATHERING: TECHNICAL SOLUTION

The main objective of the Spanish demonstrator in this regard has been to implement an automatic

process to feed the web-based tool automatically with the required data from Consumers. This should

allow connecting and transferring the required data automatically from the Iberdrola metering data

systems to a dedicated data base specifically designed for this purpose. Only the specific information

needed (no more, no less) is collected, and of course previous authorization. The data should be

collected as soon as a Universal Supply Point Codes (CUPSs) is provided. Then, the data is transfer

automatically to the mentioned secure data base from which the tool takes the data to execute the

algorithms. Consumption data should be transferred on a daily while file 2 just once.



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Moreover, the tool is provided with other source of data. It should be able to set out the data provided

by the power Spanish power system via the website of Red Eléctrica de España (Spanish Electricity

Network) (https://www.esios.ree.es/es/pvpc).

The validation process has consisted in checking if the required metering data has been transferred

correctly from the Iberdrola MDMS to the web tool secure data base during a period of 6 months. In

more detail:

Checking proper operation of the application in terms of the internal calculations made.

Checking that all external information (daily and monthly electricity consumption, electricity

prices for the following day, etc.) are properly downloaded.

Testing with real data from different users.

Based on the observations, it may be concluded that the tool meets the objectives for which it has been

designed. Apart from some punctual communication issues (not tool related) that prevented the access

to the File Transfer Protocol (FTP) to take the raw data, nothing beyond expectations has been

observed. The result has therefore been positive.

6.2.2 WEB TOOL FUNCTIONALITIES

As explained, the aim of the web-based tool is to provide Consumers with information on the benefits of

smart grids and the possibilities they offer for incorporating intelligent systems to optimise the supply of

electricity, save energy, reduce costs and enhance security. The website contains a number of useful

tools which Consumers can use to determine their consumption and identify actions that could improve

energy efficiency and financial savings.

The evaluation in this regard has consisted in checking how the web tool performs displaying the

information in each of its options (i.e. menus). Table 21, shows the main functionalities that have been

tested and test objectives. Table 21 summaries the test pass report showing some tool screen shot.

https://www.esios.ree.es/es/pvpc



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TABLE 20: SUMMARY OF THE MAIN TEST PERFORMED FOR EVALUATING THE TECHNICAL WEB TOOL PERFORMANCE

Tool

functionality Description Test objectives

Registration and

Login

Users enter their details to get

registered on the web tool. This

information is used to login and start

using the tool.

Check the full registration and login

procedure simulating different

scenarios of data entering to verify the

toll behaviour in such cases (e.g.

information that does not fit the

expected type or number of characters,

some compulsory form field is not

completed, more than one user

entering the same information, etc.).

Recovering access details, in case of

being forgotten, is also checked.

Welcome page To provide an easy and friendly

access to all tool options to the login

user (i.e. main menu, message and

consumption information).

Check the overall layout of the

welcome page to prove that all options

are visible and accessible.

Energy

consumption

display

Display different consumption

figured based of the data coming

from the smart meters (see section

6.2.1). Users have at their disposal a

variety of options view their

consumption based on different

time period (e.g. for a selected day,

daily, monthly and compare

different days).

Check that the information is well

presented for each of the option

available (e.g. no missing units, correct

and clear graphs tittles, colour code

used, etc.).

Check that the information represented

on is well refreshed once the user

changes from one graph to another (i.e.

type of graph of time period).

Setting home

equipment Using the system, users can identify

how their total consumption breaks

down between different equipment,

using theoretical statistics.

Check that the initial full data entering

required for defining the user home

profile works as expected (i.e. set the

different appliances at home and enter

more detailed information about the

appliances). Different data entering

scenarios that could happen in reality

are tested.

Check the correctness of the theoretical

breakdown of the user home

consumption after entering the

required information.



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Tool

functionality Description Test objectives

Comparison

with other

consumers

Users can compare their real

consumption with the theoretical

consumption of an energy-efficient

user with a similar home

arrangement.



available (i.e. view comparisons and

view associated challenges).

Challenges The primary purpose of the website

is to give electrical energy

consumers enough information to

allow them to reduce consumption

and create a system of rational

energy use. In the web system,

these recommendations take the

form of ‘challenges’.



available (i.e.. view challenges

completed in last year and

consumption trends, view proposed

challenges, accept proposed challenges

and view pending challenges).

Check that the challenge information is

available in the various sections of the

portal where it should be.

Display of the

energy price for

the following

day

The aim is to provide users with this

information in such a way they can

timing their consumption based on

electricity cost in each period.

Check that the energy price for all

hours on the following day is shown

and clearly presented.

Check that the user average

consumption is compared with energy

prices for the following day.



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TABLE 21: PERFORMANCE TEST PASS REPORT

Tool

functionality Performance test result

Registration and

Login

The tests performed have shown the expected behaviour of the tool after the different scenarios simulated.



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Welcome page

Regarding the information layout on the welcome page, it is thought that “Personal information” could be changed by

“Participant consumption information” for example. Moreover, the “More” push button should be aligned.

During the test, a communication issue happen in the FTP server. This avoided the tool receiving data from the FTP during

about one month (from middle June to middle July). This can be seen in the consumption graph shown below (flat profile

during the first 20 days of July). The reason was a FTP credentials change (out of the control of the demonstrator).



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Energy

consumption

display

During tests, information has been represented correctly when there was data available. However, in a specific internet

browser, the web page zoom needs to be changed to refresh the graphs (otherwise the graphs content are not displayed).



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Setting home

equipment

Tests on the setting home equipment have been successful.



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Comparison with

other consumers

It seems that the note (“estimated data”) on the right hand side graph could create some confusion to the user. The user

might wonder why having real data from smart meters it might be contradictory why the “Me” bar chart for total

consumption needs to be “estimated”.

For the moment, all data gathered from the different types of equipment is estimated. As smart meters are gradually

installed in the homes, the data for the different units will match the real situation.

Information has been well displayed in the different cases (i.e. home settings) simulated during the tests.



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Challenges

Information has been well displayed in the different cases simulated during the tests.

Moreover, energy tips displayed after clicking in each Challenge text are well valuated.



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Display of the

energy price for

the following day

After comparing a set of days chosen randomly the data displayed regarding electricity prices are the same published

officially in www.omie.es from where they are taken.

The colour code used is useful to visualise easily different price period.

Some help popup window could be added to the second graph in case de user has some doubt about it meaning.

http://www.omie.es/



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6.2.3 SOCIETAL RESEARCH

This section provides a summary of the collaboration with WP924 setting out the activities carried out in

the social sphere (more detailed information in [3]). Social dissemination activities in the Spanish

demonstration area are being conducted by Tecnalia in coordination with the Task 9.2 – Interaction

Campaigns. The information below on users' knowledge of the energy industry in general, the power

industry in particular, and of smart grids is serving to evaluate concepts and identify requi rements for

inclusion in the web-based tool.

Domestic and business Consumers have been identified as the most relevant and numerous social

groups for the Spanish demonstrator. After evaluating different alternatives to communicate more

effectively with domestic consumers, associations that represent them have been contacted first. By this

strategy the access to consumers has been proved more efficient. Therefore a series of contacts have

been established through the association that represented them as follows: FAAVVB25 (Federación de

Asociaciones Vecinales de Bilbao), Bilbao-Dendak26 and CECOBI27 (Confederación Empresarial de

Comercio de Bizkaia). In the Spanish demonstrator, the active involvement of FAAVVB has played an

essential role to facilitate the participation of domestic consumers.

The social dissemination activities of the demonstrator have been communicated personally to the

neighbourhood associations of the different districts of Bilbao during the federation meetings. A first set

of smart grids and UPGRID “learning pills” were presented and explained. At the moment of writing this

document, five specific workshops have been organised with the participation of citizens living in the

demonstrator area [10].

After an intensive recruitment effort, 146 volunteer participants (consumers residing in Bilbao) were

obtained. Based on the provenance of the sample, three groups have been established: members of

neighbourhood associations (n1=56), employees of companies participating in UPGRID without

knowledge related to smart grids (n2=55), and with knowledge and experience in this area (n3=35).

Results presented in [3] regarding the participant perception of smart grids and web tools are shown

next.

Smart Grids Awareness – Knowledge and Attitudes

The knowledge and attitudes data indicated the necessity of the households to improve their

knowledge and learn more about smart grids. Only 30% of participants have some information

about smart grids.

Regarding the attitudes about smart grids, the results indicated that:

o 46% believe that smart grids allows energy saving.

24 User Engagement, Societal Research and Dissemination of Project Results .



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o 31% believe that smart grids allow greater use of renewable energy.

o 36% believe that the smart grids promote the production and consumption of sustainable

energy.

Concerning behaviours and intention of response related with smart grids, the results indicated

that:

o 53% of participants are interested in having my energy consumption monitored through a

smart meter.

o 90% would like to reduce their energy consumption and still their bill.

o 80% would like to change their energy consumption to promote sustainability (energy

efficiency and use of renewable energy sources).

At the end, 72% of respondents will be available to participate in the future activities of the

project UPGRID.

Information Iberdrola Distribution and EVE services (web tools)

Iberdrola Distribución web tool

75% of the participants in the Spanish demonstrator survey do not know the service (web-tool)

offered by Iberdrola Distribución to consult the hourly consumption online and other figures. The

employees with knowledge in smart grids know this service and have an account (40%).

EVE web tool (Bidelek Sareak project)

More than 80% of the participants in the Spanish demonstrator questionnaire do not know the

online web tool offered by EVE through Bidelek Sareak initiative 28 called "Save at Home" to

learn about consumption and energetic behaviour. There are more employees with knowledge in

smart grids that know this service and have an account (15%).

6.3 CONCLUSIONS AND OPPORTUNITIES

Regarding the technical web tool performance, it can be said that the expected results have been

achieved. The different simulation scenario on data entering has been proved successful. Based on the

test performed some enhancements have been identified. Part of them have been already

implemented, for example making the tool available in three languages (Spanish, Basque and English)

and providing short messages (concepts and recommendations) regarding smart grid and energy

efficiency concepts in a dynamic banner at the top of the web page.

Based on the society research, residential consumers in general might be said to lack a detailed

understanding of what smart grids are and how they can contribute to energy management. Likewise,

there is a significant group of people who are interested in improving their electricity contracting and



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reducing energy consumption in their homes. Given these two factors, it can be concluded that

electricity Consumers will always welcome any reliable information provided to them. In that regard,

Consumers can use web-based tools, such the one being developed in the demonstrator to analyse their

energy consumption and assess how they have changed their habits to reduce electricity costs. This

paves the way to continue developing and disseminating these kinds of tools and being adapted to

Consumers’ needs. At the same time, it is very important to make an effort on disseminating their

existence and make Consumer find them easy to use.

Now that it has been decided on the web-based tool for the residential sector —a very large group but

one that has low energy consumption— it is believed that there is an interesting opportunity for

adapting this application for use in other sectors such as services (small supermarkets, clothes shops,

bars, etc.).



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7. ADDITIONAL LV OPERATION OPPORTUNITIES: INNOVATIVE

SOFTWARE-BASED COMPONENTS

This section presents a summary of conclusions identified so far during tests performed on a set of

innovative software-based components specified basically in WP2 - Innovative Distribution Grid Use

Cases and Functions and, in some cases developed also within this WP2 and adapted to the Spanish

demonstrator. Necessary tests to check functionalities and components objectives have been

performed. However due to the difficulties to integrate them with the DSO system in operation at this

stage, the mentioned tests have been performed with a set of offline data extracted from that system

and a virtual machine29 has been prepared with the purpose of installing as many of these components

as possible. This will allow continue performing new test in the future.

These components are focused on exploiting a series of possibilities, innovative services and

functionalities that are made affordable and boosted as a result of the high amount and diversity of data

the smart grids bring to the application of algorithms and artificial intelligence techniques. These

components are shown in Figure 65. More detailed information can be found in [2].

FIGURE 65: COMPONENTS ADAPTED FOR THE SPANISH DEMONSTRATOR

7.1 IMPROVING OVERLOAD FORECASTING

7.1.1 OBJECTIVE

Overload Forecasting System (OFS) (sometimes referred as SPS30 from its Spanish initials), is an

application that studies the observed evolution of measurements acquired by SCADA compared to some

reference day, forecasts the expected behaviour (i.e. measurements change) and notifies potential

overloads alerting the distribution network Operator in advance. The OFS design has been reviewed

29 A virtual machine has been prepared with the purpose of installing as many of these components as possible. Windows 2012 R2, 30 0GB and 16GB RAM.

30 SPS stands for Sistema de Previsión de Sobrecargar in Spanish.

Overload forecasting system in SS

MV State Estimation SS simultaneity factor

estimation

Demand response simulator

Support for the Maintenance Crews

SS Load and Generation forecasting



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with the aim of achieving a relevant performance (data management and processing) improvement. This

is motivated by new data availability from SSs due to the progress ive installation of AMI that bring

telecommunications to previously uncommunicated SS and enable not only measurements at the MV

side (process started years ago) but also to the LV side of distribution transformers.

7.1.2 EVALUATION

Focused mainly on:

a) Application accuracy improved with a more efficient data interchange schemes (both in terms of

polling timing and the amount of record transferred in each interaction) and the application of

better forecasting algorithm performance.

b) Operator satisfaction degree coming from this mentioned accuracy, additional polling

configuration options and notification means.

The FPS web application is executed from a corporate intranet application server and integrated with

Iberdrola’s authentication and authorization server. Several access roles are considered.

The DMS operator is able to review the set of alarms, check them comparing the real

measurement values with both those from the reference day and the forecasted evolution and act

in consequence. If needed, the DMS operator might vary the reference day or the applied

thresholds for a new forecast process.

An authorised user is able to select measurement points, visualise them along some time period

and retrieve these datasets as .csv files.

7.1.3 CONCLUSIONS AND FUTURE OPPORTUNITIES

The following main conclusions and opportunities have been identified:

It is a tool that is used daily in the control centres. It facilitates the Operator duties generating

messages (i.e. alarms) that inform about the foreseen overloads. For this reason, it is not dismiss

the opportunity of sending this information to the SCADA in the future.

It seemed advisable to modify the AppLinkDMS module [2] in order to achieve faster results and

shorter execution times so the number of treated measuring points would be extended

progressively to include data from SSs within acceptable process time requirements. Otherwise,

DMS operator ordered application executions would become unacceptably slow and useles s for

the intended purpose.

The AppWeb module [2] also required access to the measurement data repository but with a

reduced number of simultaneous points so a gain of a tenth of a second per measuring point

would not deserve any attention nor would provide any value.

Regarding the optimal grouping strategy of electrical measurements to be retrieved a conservative

approach was advised. The review of the sizes of the fields used at Historical Information System (

HIS) database function (up to 200 characters for point list entry) and tables (up to 10 characters

for point number) and obtained times suggested that grouping measures in groups of 15 elements

could be enough. Whatever the real size of each point code was, there would be room for the



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complete string of characters without any further check. The elapsed times for groups of 20 and

25 measuring points could be biased because many of those points have sparse datas ets.

Comparative and cooperative analysis of the results of this tool with the results of other grid

monitoring and managements systems (OMS, network management system, state estimation

tools, etc.) would allow to identify and check grid sections and assets under stress improving grid

supervision, maintenance and planning.

7.2 IMPROVING MV STATE ESTIMATION

7.2.1 OBJECTIVE

The objective of the MV state Estimator is to calculate the most likely state of the network for a certain

instant in time. The state of the network includes for a specific time, the values of: voltages, power and

current injections at buses31, and, power and current flows at network branches 32. State estimation

calculations use, as the main input the measurements collected from the field devices and take into

account their accuracy for calculating the most precise network state. The innovation comes from the

use of a weighted least squares algorithm capable of handling the distribution network characteristic.

Contrary to the current approach where load allocation techniques are used, the deployed state

estimation techniques use information form the full set of measurement devices installed in the

demonstrator. In this way it is able to provide insights about the performance of the monitoring system

while improving the accuracy of the estimations.

7.2.2 EVALUATION

The MV state estimator has been executed as an off-line tool using historical measurement data

provided by Iberdrola of one subnetworks (i.e. Deusto TF-2 132 KV). The analysis includes the following

main points:

Normalised errors: The normalised error indicate how far are the estimated values from the

measured values scaled with the accuracy of the measurement. Values between -1 and 1 can be

considered as normal values while values higher than 1 or lower than -1, indicate that the

accuracy range should be analysed since they may indicate potential errors in the network model

or the measurements themselves.

Absolute errors: The difference between the measured value and the estimated ones gives an

indication about the level of correction made by the estimator. High errors indicate that the

31 A bus corresponds to the set of nodes that, in the considered network state, are connected together through any type of closed switches or equipment with zero impedance. Buses change as the network topology changes (i.e., switches, breakers, etc. change state).

32 A branch is a subset of a network, considered as a two-terminal circuit, consisting of a circuit element or a combination of circuit elements. Each terminal of a branch is connected to a bus. Typical branches are feeder segments and power transformers.



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estimator needs to modify the measured values and provides a measure on the benefit of having

a state estimator respect to only having the measured values.


The MV state estimation component has been successfully developed and tested in the Spanish

demonstrator. The performance of the developed estimator is good enough to be used with large time

series of measured values. The algorithm is able to converge and produce information about the

estimated values and different error indicators.

Using a rich user interface, several off-line analyses have been done over the state estimation results.

The analyses have been focused on the interpretation of the differences between the estimated values

and the measurement values. These analyses yield useful information allowing the identification of

potential inconsistencies in measured values.

The state estimation results indicate also the high potential of applying state estimation techniques in

the distribution networks for correcting measured voltage and power values.

7.3 IMPROVING DSO DECISIONS BASED ON DEMAND SIDE ESTIMATION

7.3.1 OBJECTIVE

The demand response simulator component is intended to be used by the DSO for estimating the effect

of Demand Response (DR) programs in the aggregated consumption profiles of residential Consumer

clusters. This simulator is able to calculate the modification in the aggregated consumption profile of

Consumer groups when different energy prices or other control actions are taken over them.

Specifically, this simulation tool addresses the indirect control strategies based on dynamic pricing. The

Demand Response Simulator component could allow any Energy Market actor (i f permitted by

regulation) to analyse possible Consumers behaviour depending of different control signals, especially of

energy prices.

7.3.2 EVALUATION

From the technical point of view, the installation and testing of the tool run properly and the estimation

algorithms worked quite accurate.

From the Consumer behaviour observed, it can be said that Consumers providing flexibility tend to

reduce heating/cooling energy consumption and delay the starting times of shiftable appliances from

peak price periods to valley periods. The amount of flexibility provided depends on the price sensitivity

of the Consumers, the higher the price-sensitivity, the higher the amount of flexibility provided. In

addition to this, this flexibility can come from shiftable loads, from thermal loads or from both, as a

function of the desired trade-off between price sensitivity to cost, to control of shiftable loads and to

control of thermal loads.



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No relevant performance analysis has been considered due to novelty of the tool and the lack of actual

data available about the Consumers home loads and preferences, which were simulated.

In general and from the conceptual point of view, it can be stated that the results of the analysis of this

tool is satisfactory and promising, even considering that some of relevant data had to be simulated (the

detail of the Consumer home loads and profiles of variable.


The results of the tests show that Consumers providing flexibility tend to reduce heating/cooling energy

consumption and delay the starting times of shiftable appliances from peak price periods to valley

periods. The amount of flexibility provided depends on the price sensitivity of the Consumers, the higher

the price-sensitivity, the higher the amount of flexibility provided. In addition to this, this flexibility can

come from shiftable loads, from thermal loads or from both, as a function of the desired trade-off

between price sensitivity to cost, to control of shiftable loads and to control of thermal loads.

It is important to take into account the payback effect that would be produced when the control actions

finish and the appliances return to their normal operation modes. At an aggregated level, this power

synchronization effect may cause a significant peak in the power consumption and may affect adversely

the operation of the electricity grid. Consequently, the DSO should apply certain strategies to try to

minimise it. In any case, the results of these simulations are only for validation purposes as they are not

based on actual data and therefore the amount of payback generated should be further studied.

As a conclusion, it can be stated that the developed component provides an effective approach to the

challenge of estimating the aggregated consumption profiles of a group of Consumers (cluster) as

response to variable electricity prices. This is very important for the DSO in order to define the strategies

to be followed in terms of market participation and Consumers’ portfolio optimization.

As an opportunity, it has been identified the possibility of adding other simulation criteria, different

from the energy price, especially those options based on Flexibility and grid operation, performance and

quality improvement. In a medium term scenario, and according to the European Commission Clean

Energy (Winter) Package provisions, it is supposed a more relevant participation of the

Consumers/Producers in the electricity market being an active actor in some of the grid O&M processes.

In this new role, it is expected this grid Consumers to declare and make accessible their home loads and

generation sources to be manageable for the optimization of the grid operation. In that scenario, this

kind of Consumer consumption/production estimation tools, being able to access to reference

information from these homes DER, will be of great relevance, not only for the retailing market, but also

for the optimization of the planning and operation of the grid.



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7.4 IMPROVING LOAD DISTRIBUTION BASED ON THE SIMULTANEITY

FACTOR ESTIMATION

7.4.1 OBJECTIVE

This SS simultaneity factor estimation component consists of a statistical algorithm that estimates the

load Simultaneity Factor (Ks) in the scope of a SS. Several issues, such as the network components and

Consumers characteristics (e.g. load curves and contracted power) are considered when computing the

simultaneity factor using this algorithm. This component exploits mainly data gathered currently by

existing smart meters. Ks is defined as a probability measurement of the coincidence of individual

maximums with the maximum of the aggregated load, in other words, it is the ratio of actual kWh used

in a given period, divided by the total possible kWh that can be used in the same period at the peak kW

level.

The formula which defines the simultaneity factor is:

𝐾𝑠 = 𝑃𝑚𝑎𝑥

∑ 𝑃𝑚𝑎𝑥,𝑖𝑁𝑖=1

EQUATION 1: SIMULTANEITY FACTOR

Where Pmax represents the peak load and Pmax,i represents the peak load of the Consumer i. The Ks of a

certain electrical network, a certain distribution transformer or a certain SS relates to the load

characteristic of the Consumers to belong to this electrical network, distribution transformer or SS and

the amount of these Consumers.

7.4.2 EVALUATION

Optimal Phase Swapping in LV network based on smart meter data. Based on DSO requirements to

properly address the Optimal Phase Swapping task [19]. That is, allocate Consumers to certain LV feeder

phases based on their previously calculated Simultaneity Factor.


It is a matter of common experience that the simultaneous operation of all installed loads of a given

residential or industrial installation never occurs in practice, i.e. there is always some degree of diversity

and this fact is taken into account for estimating purposes by the use of a simultaneity factor (K s).

The simultaneity factor is the ratio of the maximum demand of a group of loads, or part under

consideration, to the sum of the individual maximum demands. The factor Ks is applied to each group of

loads (e.g. being supplied from a distribution or sub-distribution board). It is concluded that the

statistical Ks model can be used by DSOs to assess the impact of adding a new set of supplies points (i.e.

Consumers) on a given LV feeder. In this sense, the Spanish demonstrator has perceived the necessity of

having an optimization algorithm capable of distributing these new Consumers to LV line phases with

the objective of minimizing the Ks and thus avoiding deep valleys into the aggregated load curves.



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Therefore, a novel tool for phase swapping in LV distribution networks is adapted to the demonstrator

takin into account these Consumers individual contributions to the aggregated consumption curve using

real hourly measurements. Then, this functionality provides a realistic procedure for optimizing the

topology of LV distribution networks, regarding the connection of Consumer at LV line phases

minimizing, statistically, the Ks factor.

From a technical point of view is concluded that knowing the load pattern, the consumption habits are

known as well. As per this definition, the value is always ≤ 1 and can be expressed as a percentage of

total loads that contributed to peak consumption. Usually it decrease as the number of connected load’s

increases, also if the maximum consumption does not match with the maximum of the aggregate signal

(sum of individual maximum consumptions), the Ks decreased. The real objective when trying to

minimise the Ks is flattening demand redistributing the consumption by shifting load to decrease

demand peaks while filling in troughs. Flattening demand implies reducing the difference between the

peaks and troughs in a LV distribution network usage, thereby creating a fletter usage pattern that

lessens the deviation from the average usage. Demand flattening has the potential to benefit

Consumers as the electric grid becomes smarter and more efficient, since peak demands have a

disproportionate effect on grid capital and operational costs, including transmission, generation, and

fuel costs. For instance, demand flattening significantly reduces transmission and distribution losses,

which account for nearly half (47%) of residential energy consumption [3], since these losses are

proportional to the square of current.

As an opportunity, it has been identified the possibility of extending the main calculations applied for

determining the simultaneity factor to other processes addressed to the optimization of the Consumer

connection to the feeders and phases in SSs. That is: Identification of Consumer unbalanced connectivity

in a due SS.

Definition of the optimal Consumer connection configuration for new or already existing

registrations.

Estimation of the cost required for the adequate reconnection of Consumer in a SS.

Starting from a specific budget, the identification and prioritization of the Consumers that would

be reconnected for to achieve a specific improvement of a SS connection configuration.

7.5 ENHANCING THE OUTAGE MANAGEMENT AND THE SUPPORT FOR

THE MAINTENANCE CREWS COMPONENT OBJECTIVE

7.5.1 OBJECTIVE

This component represents an attempt to test the potential advantage of a combined analysis of the

smart grid data from SSs and AMI for the characterization of the grid assets operation and failure as the

reference for an adaptive maintenance planning and for an optimal outage management and

maintenance crew coordination and support.

The implemented component carries out the following main functional blocks:



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dynamic information acquisition and processing,

static information configuration, risk and reliability assessment

optimal planner for maintenance scheduling

7.5.2 EVALUATION

This component was verified as a standalone application fed with some demo data, both dynamic data

from smart meters and SS sensors and static data for maintenance resource information, network assets

and network and assets model. These data belonged to a SS located in the Spanish demo area.

With these data the tool generated different results about asset replacement scheduling for the

transformer and lines of that SS, network single line diagrams, foreseen failure curves and propositions

of maintenance scheduling for those assets.

This information was shared with representatives of the maintenance function stating the promising

potential of the tool.

Some deviations can be observed in the results of the tool, especially in the line diagram model with

respect the actual one. This is mainly due to the present lack of some information about some grid

assets, especially feeders, that is being completed during the demo completion.

Additionally, proper historical data of assets failures are not completely available for an accurate

preventive asset maintenance scheduling but the proposed plans obtained with simulated historical

failure and the operation data seem to be consisting.


Tool to be considered for the next future when the MV/LV data would be complete and stable, specially

the data related to the network topology model and the historical operation and failure assets data that

will allow to simulate the operation of each asset, to estimate its potential failures and to define

preventive maintenance plans individually for each asset and even fora better grid planning definition.

7.6 LOAD AND GENERATION FORECASTING IN SECONDARY SUBSTATION

7.6.1 OBJECTIVE

The load and generation forecasting component provides the grid manager with the analysis, modelling

and forecasting of the electrical energy consumption of Consumers and/or generators (including the

role of “prosumers”) aggregated at distribution transformer level in SS.

The main functionalities provided by the component are:

a) The analysis of Consumers data that gives insight on its present behaviour and to characterise it

in order to be able to foreseen that behaviour in the future.



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b) With the previous analysis integrated to meteorological information, the forecasting of load and

generation of DERs connected to the grid that is considered a valuable outcome for energy

management at the SS level. This information is important for the DSO, as it can be used to

predict the status of the system and avoid faults or other events.

The objectives of bringing this component to the Spanish Demo were basically:

To check the accuracy and performance of forecasting algorithms in the domain of consumption,

production and “presumption” of the Consumers connected to the grid.

To start considering to incorporate on regular basis external information, meteorological data and

forecast basically, to the grid O&M systems.

7.6.2 EVALUATION

Spanish demo energy consumption and production data was used from a SS with Consumers and

Prosumers with detail of the geographical location of the DERs estimated. This information was

completed with meteorological measurements and forecasting, and the reference working calendar

related to the meteorological information.

With those data, the tool performed properly from the technical point of view providing coherent

results, even considering the provisional nature of the consumption and generation information applied

for comparison.


The tool can clearly help in the estimation of the SSs work conditions in expected situations of gri d

stress. Even, its results can be analysed in combination and coordinated to the results of other tools like

the Demand Response Simulation tool or the Overload Forecasting System. This would be a way of

checking in the future the performance of these tools allowing the updating of the algorithm

configuration and tuning to the changing data conditions of the grid.

It is worthy to highlight also the benefits of integrating meteorological information in the grid estimation

processes, more relevant even in the expected medium term scenario of massive DER connected to the

grid.



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8. BUSINESS PROCESSES IMPACT

8.1 LV OPERATION AND MAINTENANCE

Iberdrola organises the network operations in five regions 33. The Spanish demonstrator is under the

responsibility of the North Region34 which control centre is located in Iberdrola’s premises in Bilbao.

Network operation personnel are responsible for the LV network in a defined region. This includes both

planned and unplanned works, trouble calls and incidents. They have a territorial organization (i.e.

Distribution Territorial Units (DTUs)) that facilitates a quicker response to faults and incidents and also

reduces travel time for routine work. Each of these units has a main depot, providing accommodation

for office based staff and stores to meet the local operational requirements. Typically there is a team

leader (LV Maintenance Supervisor) under responsibility of all field staff (LV Field Engineers or LV Field

Crews) in each particular DTU. LV Field Crews can be either belongs to Iberdrola Distribución or to

contractors. During working hours the LV Maintenance Supervisor investigates, prioritises incidents and

distributes the tasks to LV Field Crews in an optimised manner. Unplanned faults and incidents are

automatically assigned to the teams in the field according to the automatic choice made by an algorithm

within the Work Orders Management System (WMS). Outside the normal working hours, the Field

Crews work autonomously to cover urgent unplanned outages. In case of UPGRID, the distribution

network is covered by two DTUs : Bilbao and Baracaldo (covering the areas delimited by the red and blue

contours respectively in Figure 9). Thanks to the work developed in the Spanish demonstrator regarding

the LV NMS (desktop and mobility solutions) new opportunities for LV O&M can be evaluated.

Currently, LV incidents in the Iberdrola’s distribution network in general and in the demonstration area

in particular, are managed following a defined flowchart in order to restore the service to the affected

Consumers as quickly as possible. Incidents are registered in the existing Outage Management System

(OMS) triggered from different origins, mainly Consumers who call saying that they are suffering a

supply outage or through manually entries done by Control Centre Operators. Then, Field Crews are

assigned to each incident manually by the control centre staff or automatically thought the existing

mobile solution. Then, Field Crews are in charge of locating, assessing and restoring the service. They

rely on the communication with the Control Centre that use the information they have available from LV

network what, before UPGRID, is not as complete and accurate as it is for MV. This fact introduces some

inefficiency in the process that lead to pass less precise information passed to Consumers. Moreover,

each LV incident restoration report does not provide detailed accounts of the intermediate actions

taken to solve an incident and the number of Consumers that have restored the supply (i.e. lack of

information regarding each individual interruption). Before UPGRID, only two significant times are

registered: the incident starting time (i.e. mainly first Consumer call reporting the lack of electricity

33 Each region has one Distribution Control Centre managing approximately 2 million supply points (apart from the East region that has two for the higher number of supply points).

34 Geographically, the North region covers a total of five provinces: Vizcaya, Guipúzcoa, Araba, Navarra and La Rioja.



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supply) and the incident closing time (i.e. when the service is recovered to the last Consumer affected).

The work developed in the Spanish demonstrator is intended to enhance the latter process mainly by

providing access to update information at any moment to all actors involved. That is, incorporating

smart meter events to trigger incidents automatically, using the offered LV NMS operation ca pabilities

(e.g. tracing features, smart querying and comprehensive event management) and integrating it with

other Iberdrola third parties systems (e.g. GIS, OMS, AMI and SCADA). Moreover, these developments

allow having structured information about the evolution of an incident what facilitates real time

knowledge about its status being of value for O&M and to inform Consumers about it. Then, LV

incidents can be managed more effectively and efficiently as explained, among other benefits in

Chapters 2 and 3.

Iberdrola is evaluating subcontracting all the work related to LV. In this sense a pilot35 was launched

with successful results that would support this new business process. To be successful, new tools are

required to allow Field Crews complete the full cycle that the LV works and incidents involve. It is here

where UPGRID Spanish demonstrator development plays a relevant role. The LV NMS would be the

pivotal tool to do that. This makes the system necessary. Therefore, Iberdrola is planning to have a LV

NMS deployed and in full operation covering the entire LV network under its responsibility in Spain

before 2020 that will be based on the results obtained in the UPGRID demonstrator.

The philosophy would consist in equipping Field Crews with a tablet. These people can be DSO

personnel or subcontracted. The mobile device will allow them performing analysis about the incident

(e.g. requesting meter measurements on demand) before moving to any place along the LV network to

pinpoint the origin as much accurately as possible. This clearly will reduce the displacement for example

in those cases when the incident is originated in an installation which is not under the responsibility of

the DSO. It has been observed, a corroborated with demonstrator data, that around 40% of the calls

that arrive to the DSO are not related to incidents under its responsibility. Apart from the Mobile filter

applicability, the call centre filtering procedure will be reviewed to minimise the number of calls that

should not be arrived to the Field Crews. All this will add even more efficiency on the business process.

Moreover, as mentioned in this document, Field Crews will be able to reflect all field works in the mobile

device being storage in a central system accessible by all the maintenance responsible. Having the

possibility of performing DPF, it will allow them evaluating different alternatives to restore the

electricity supply after an incident.

It is expected a single system (i.e. the LV NMS) with the full Iberdrola LV network being the data

centralised in a unique data base. There will be central workstations from where maintenance

responsible will access to, for example, monitoring the field work. Above all, the main contribution will

be the mobile solution to manage the LV works and incident from the moment an event is recorded

until they are closed. Moreover, based on the Field Crew location, the work order will be automatically

dispatched to the closer one.

35 This is out of the scope of the UPGRID project.



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Based on the UPGRID Spanish demonstrator experience those Field Crews that have used the LV NMS

solution are satisfied. They considered that the tool is useful. During the operation test the Field Crews

have used in parallel the current mobile devices [a mobile phone in which received and close the LV

incidents; and a PC to have access to the graphical interface of the GIS (static view of the LV network)]

and the UPGRID LV NMS Mobile solution. In the near future they will one have one single tablet.

8.2 PRIME MULTISERVICE

The Spanish demonstrator has developed several activities in order to identify the suitability of remote

control over PLC PRIME network, taking into account the standard operation over current PRIME

networks, which is AMI data transport (see section 4.2). The approach is testing current RTUs connected

to a PRIME gateway, in order to test this solution for future RTUs, which will support PRIME technology.

LV remote control extension is assumed within the smart grid functions. MV remote control is well

integrated in the electricity grid operation, although not present in all SS. Its purpose is to get

information of the grid as well as to operate the grid elements (e.g. switches) remotely and safely.

Remote controllable points in the LV grid will allow the same mode of operation in this LV segment of

the grid. Remote control traffic could make use of current PRIME network in order to be transmitted

sharing the channel between AMI and remote control traffic.

If the SS does not have enough GPRS/3G coverage to let the router establish a good connection with the

AMI Head System, DSO would have to deploy an alternative transmission method (often expensive),

such as a proprietary optical fibre link. Within the scope of UPGRID project it has been demonstrated

that using the GTP capabilities to provide an IP connection over PRIME network, DSOs can avoid the

investment in other transmission methods. Remote access would therefore be offered from a meter

room nearby that would have enough GPRS/3G coverage and GTP would offer the last step to the AMI

data concentrator over IP over PLC PRIME.

A multiservice PLC PRIME network as deployed in the scope of the project would enable the LV backup

feeder smart switches as a future business process. Although there were no SS in the demonstrator area

that allowed field deployment of this concept, the idea can be supported with the capabilities

demonstrated within the project.

The approach followed here is to use remote control application (IP over PRIME) in order to manage this

feeder switching and therefore SS switching. This is an alternative future approach that would be

applicable in scenarios where mesh LV networks are available. It requires SS with LV backup feeders

where remote control for smart-switching is applicable. This means that there should be LV points in the

network where a second LV feeder from a backup SS arrives. This kind of LV grid allows switching to a

backup SS in case of supply faults or anomalies in its main SS.



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8.3 PRIME MANAGEABLE: REAL TIME AMI FAULTS DETECTION

Real time information is needed to optimise the operation of the grid providing instantaneous

information of the meters connected to the SSs. SNMP based Network Management System (NMS)

specified, developed and deployed within the project improve AMI fault detection available at the

moment.

This implementation over a massive PLC PRIME deployment would offer detailed PRIME information.

The use of this information allows the detection of faults in the feeders (e.g. broken conductors),

voltage control in the distribution transformer, and tampering detection. Some of these applications are

not feasible at a reduced cost with non-PLC technologies.



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9. CONCLUSIONS

The present document highlights the evaluation and opportunities identified during the performance of

the UPGRID Spanish demonstrator for each of the working lines covered on it (see Figure 7). Detailed

conclusions can be found along the chapters that form this deliverable which are complemented with

those included provided in [1][2][3]. A summary of them is presented next.

First at all, the LV monitoring and controllability enhancements deployed in the demonstrator (e.g.

smart meter data utilisation, LV sound network representation, LV NMS and LV control over PRIME)

contribute to have more accurate knowledge and management capabil ities of the LV network in near-

real time, being the monitoring capability one of the key enabler that allows the rest of new

functionalities.

Results and experience obtained in the UPGRID Spanish demonstration are qualitative and quantitative

steps forward to the LV O&M business process more decentralised oriented where all staff involved has

real time access to update information. In this scenario, that has already started taking shape, the

demonstrator has confirmed the need of managing a better representation and O&M of the LV network.

Firstly, from the control room point of view; secondly, and most important, it has also been confirmed

the benefits of a LV NMS that provides Field Crews with a Mobile solution incorporating a series of

capabilities. This has started introducing value added (to DSOs, Consumers and other electricity sector

stakeholders) and increase the efficiency on LV O&M. The demonstrator has facilitated the definition of

this set of functionalities. Tests results and feedback received from field users show encouraging insights

to back the expectations articulated at the beginning of the demonstrator to continue working in this

direction. The latter feedback indicates that there is still room for further improvement as well. This has

allowed identifying new enhancements and opportunities to be implemented, what stresses the

importance of having a flexible system to add new requirements. All this is already being gathered in a

system specification that will be the base for the LV NMS that will cover the full Iberdrola LV network.

The LV NMS developed in the demonstrator has been able to manage successfully the increase of data

arisen after approximately doubling the original intended LV network covered by the system. Then, it is

concluded that extending the LV NMS to new areas could standardise the system for the whole

Iberdrola, and business processes are not tied up in specific geographical areas, so it should be possible

to extend the current demonstrator experience and know-how.

Main Iberdrola LV NMS users that can now benefit from the new capabilities of the demonstration are

the LV Maintenance Supervisor and LV Field Engineer. The LV Maintenance Supervisor is responsible for

the investigation, prioritisation and distribution of incidents. The Field Engineer works in a crew handling

a mixture of outages and work orders. LV Maintenance supervisors can now: ensure that the asset and

topology information of the LV network is accurate and up to date, introduce temporary changes,

manage unplanned and planned LV outages and investigate LV outages. LV Field Engineers can now: be

assigned outages, introduce temporary changes, manage unplanned LV outages, manage planned LV

outages, investigate LV outages, re-configure feeders.



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The deployment of multiple interfaces between LV NMS solution and Iberdrola’s existing systems

provides the LV NMS user with relevant information. Some of them are real time interfaces and are

reflected on the LV diagram. The LV NMS user, either using the Desktop or Mobile solution, has a full

understanding of the real status of the LV network at any point in time. The LV diagram conveys visual

information to the user who is better equipped to take decisions regarding the network operation. Plus

the ability to poll the smart meters on site from the Mobile device enhances the information.

The UPGRID Spanish demonstrator contributions improve PRIME subnetwork capabilities. The solutions

validated in the demonstrator have a direct impact into the DSO operation and final Consumer. The aim

has been mainly to take advantage of the telecommunications infrastructure that is deployed for smart

metering purposes offering further information and services that increase its value and usability.

Specific developments have been done in order to validate these functionalities (e.g. LV remote control

can be enabled over existing AMI deployments).

The development of a LV grid remote control over AMI PLC PRIME infrastructure is feasible. A

multiservice PRIME subnetwork can be enabled, as demonstrated during the deployment and testing

phase. The conclusions of this characterization determine that IP over PRIME is a feasible alternative to

transport RTU control traffic using PLC PRIME as a channel. PLC PRIME specification has been analysed

and a ticket proposal has been opened within the PRIME Alliance in order to optimise remote control

data exchange over PLC PRIME. It has been critical to maintain PRIME requirements of a standard and

interoperable network. Within the demonstrator a new LV Remote Control Profile is proposed with its

own capabilities.

This UPGRID multiservice subnetwork requires a higher level of monitoring and knowledge of the PLC

channel. This PRIME monitoring is the first step that enables a PRIME multiservice network. This is a key

enabler then for the control traffic exchange over PLC PRIME developed also in the scope of UPGRID

demonstrator area. A SNMP protocol for managing PRIME devices has been designed, specified,

developed and validated successfully within the demonstrator. The development and integration of

these elements have been validated both in laboratory and in the field (demonstrator area). At this

stage, with the implementation done, PRIME monitoring is ensured.

Regarding smart meter event analysis, it has proven to be promising to network operation. However,

there is still scope to take full advantage of them. On the one hand, the smart meter events offer the

DSO the capability of automatically receiving information about LV network incidents. In the light of the

performed survey, this information could be valuable to enhance the network operation. On the other

hand, using this information involves the technological challenge of dealing with a high quantity of data

which should need the application of big data analytics techniques. The methodology tested for event

analysis will be used for identifying the most useful functionalities and set up parameters to specify,

based on that, new modules in the MSMS.

The technical performance of the developed web tool for managing energy consumption rationally by

Consumers has behaved as expected. Some enhancements have been identified for future versions.

From the social point of view of this line of work, it has been seen that in general, the public has a fairly

limited understanding of smart grids. The same is true of their knowledge of the electricity market and

the way electricity retail prices are set. It therefore seems clear that providing ordinary people with



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tools that help them to understand their current consumption and the cost of electricity in their home

or workplace, could be useful for decision-making in this regard.

It is true that the decisions made using such web-based tools often do not lead to major energy and

economic savings in individual homes. However, when viewed from the perspective of society in

general, these small individual contributions do help to save energy and to reduce the overall energy

consumption as well as flattening the electricity demand curve. It is stressed the importance of

providing Consumers with more and better information on energy in general and electricity in

particular. This will enable them to decide what domestic appliance they want to buy and how they use

it at home. It will also allow them to manage the way they contract their electricity supply. It is also

important to promote the installation of new units that will give additional information on energy use.

Smart meters are already being installed and will be in widespread use in the near future. To sum up,

society needs to be well-informed and have tools that help reduce energy consumption and cut energy

bills. The use of web-based tools, such the one being developed in the demonstrator, can support this.

With respect the technology-based innovation tools, some conclusions can be issued:

The opportunity and potential benefits of the application of advanced data processing

techniques, especially those related to artificial intelligence and data analytics, to the

tremendous amount of data produced practically in all segments of the MV/LV grid.

The promising benefits of the progressive introduction of already presently affordable and

reliable estimation and forecasting processes that allow to foreseen in advance s pecific

situations or behaviour of the grid, the connected DER to it and the different electricity market

actors. This advanced knowledge will clearly support and help in the DSO decision taken for a

proper grid management and planning and an active and effective participation of other related

actors, specially the Consumers and Retailers.

It is considered interesting the possibility of performing analysis of combined data coming from a

different grid segment to that studied. This is especially applicable to the AMI and smart meters

events that, as demonstrated in the Spanish demonstrator, can be applied to several processes

of grid O&M (phases an lines identification and connectivity, outage management, SS

simultaneity factor estimation, overload estimation and detection, etc.) and DER

characterization.

Due to that capability and opportunity of several applications using the same set of data, the

(CIM based) standardization has been observed as crucial in order to maximise the reutilization

of those data and the scalability, replicability and interoperability among those applications.

Last, but not least, it is interesting to summary the impact of the demonstrator results on partners a part

from Iberdrola. They are as follows.

GE, as provider of the LV NMS solution, has gained a better understanding of the Iberdrola IT and OT

environments, and the Iberdrola business processes regarding how to operate the LV network. This

knowledge is key for GE as an input to set up the future strategy of GE GIS and ADMS products suit

roadmap. At the same time, GE has certainly managed to improve current releases of Smallworld (GIS)

of PowerOn (ADMS) product suites, as a real outcome of UPGRID project, mainly the following: The

product capabilities for CIM data format importing of electrical networks into the LV NMS (a real and



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significant extension of a LV network diagram, using CIM format, has been successfully imported in the

demonstrator). The product data model and end user interface to manage smart meters data coming

from AMI, and the new capabilities of the mobile solution to manage temporary elements (cut and

jumpers) and switching operations (insert/eliminate fuse) in the field, improving the interface between

the Desktop and Mobile solutions. This experience helps GE products to be better serve current

requirements of the DSO´s, in the area of O&M of LV grids; from the perspective of both key users:

control room engineers and field engineers.

ZIV, as equipment manufacturer and provider, has the opportunity to evolve existing and standardised

products and launch new ones that include additional applications based on the UPGRID demonstrator

outcomes (e.g. PRIME GTP). The SNMP monitoring tool allows building new competencies inside ZIV.

Turn-key solutions will be demanded in the future and this knowledge will be necessary. This facilitates

ZIV being, in case of UPGRID project scope, on the technology edge of monitoring and controllability LV

solutions.

Tecnalia, as a non-for-profit RTD institution, will take their designs and developments (especially in the

scope of smart meter events analysis automation, load/consumption curves analytics and Consumer

behaviour Active Demand Response simulation) as know-how and reference implementation assets to

be applied in future projects. There will be a special attention in disseminating and transferring these

technological assets to the Small and Medium Enterprises (SMEs) industry in the domain of the smart

grids.

EVE, as an energy agency will be able to use the consumer empowerment tool resulting on the project.

The tool can evolve further with new functionalities and be adapted to extend its use to other type of

users apart from the residential Consumers.



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REFERENCES

UPGRID DOCUMENTS

UPGRID project deliverable D3.1: Tools suit for the Advanced Real Time LV network representation [1]

[confidential]

UPGRID project deliverable D3.2: Tools suite for the smart control and operation of the LV Grid [2]

[confidential]

UPGRID project deliverable D3.3: Customer Capacity building web-based system [confidential] [3]

UPGRID project deliverable D1.1: Report on Technical Specifications [confidential] [4]

UPGRID project deliverable D2.1: Functions and specification of tools for improved supervision and [5]

management of MV/LV grid [confidential]

UPGRID project deliverable D2.2: Report on Services provided by DSOs to the retail market [public] [6]

UPGRID project deliverable D2.5: Conclusions of load and generation forecasting models [public] [7]

UPGRID project deliverable D2.6: Software of Load and Generation Forecasting [confidential] [8]

UPGRID project deliverable D8.1: Report about KPIs analysis and methods of comparison [public] [9]

UPGRID project deliverable D9.1: Targeted Social stakeholders segmentation and analysis [public] [10]

EXTERNAL DOCUMENTS

Real Decree RD 1955/2000. https://www.boe.es/boe/dias/2000/12/27/pdfs/A45988-46040.pdf (in [11]

Spanish)

J. García, 2016, “Beyond Smart Meters: Management of the LV network”, CIGRE Paris 2016, [12]

Preferential Subject 2 - Sub-Topic 3: Impact of developments in energy technology, IT, big data, and

further trends in distribution systems, C6-206.

L. Garpetun, 2014, "The challenge of adapting your AMI-system for LV-grid monitoring", CIRED [13]

conference, Poster session, Theme 3: Grid operation and congestion management, 0244.

PRIME Alliance, http://www.prime-alliance.org/ [14]

https://www.boe.es/boe/dias/2000/12/27/pdfs/A45988-46040.pdf

http://www.prime-alliance.org/



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REAL DECREE 1955/2000, dated 1 December, it includes the zone classification [15]


ORDER IET/290/2012, dated 16 February, amending ORDER ITC/3860/2007, dated 28 December, [16]

which reviews the electricity rates as of 1 January 2008 in relation to the meter replacement plan.

https://www.boe.es/diario_boe/txt.php?id=BOE-A-2012-2538

“Technical specification of type 5 meters with remote management capabilities and time [17]

discrimination”, 2011.

Tableau Desktop https://www.tableau.com/ [18]

Mendia, I., Gil-López, S., Del Ser, J., Bordagaray, A. G., Prado, J. G., & Vélez, M. (2017, February). [19]

Optimal Phase Swapping in Low Voltage Distribution Networks Based on Smart Meter Data and

Optimization Heuristics. In International Conference on Harmony Search Algorithm (pp. 283-293).

Springer, Singapore.


https://www.boe.es/diario_boe/txt.php?id=BOE-A-2012-2538

https://www.tableau.com/



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LV NMS MONITORING INFORMATION DISPLAYED Annex I.

The following figures (Figure 66 to Figure 73) present some examples when the LV NMS user is provided

with real or near real time data which is reflected on the LV network diagram.

FIGURE 66: MV VOLTAGES (VIA ICCP INTERFACE)

FIGURE 67: MV ENERGISATION STATUS (SS ENERGISED/DE-ENERGISED). IN THIS CASE THE UPPER “FAKE” SWITCH IS

OPENED AND ALL THE LV CIRCUITS DOWNWARDS ARE WITHOUT ENERGY SUPPLY (WHITE COLOUR)



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FIGURE 68: DISTRIBUTION TRANSFORMER SUPERVISION METER EVENTS ARE DISPLAYED WITH A FLASHING MARK

(İEVENTO!) NEAR THE TRANSFORMER SYMBOL

FIGURE 69: CONSUMER SMART METER EVENTS ARE DISPLAYED AS A PSEUDO CONSUMER CALL ON NEAR THE FB SYMBOL



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FIGURE 70: DISTRIBUTION TRANSFORMER SUPERVISION METER INSTANTANEOUS VALUES ARE DISPLAYED NEAR THE

TRANSFORMER SYMBOL

FIGURE 71: PENDING MAINTENANCE WORK INDICATION (“AO” TEXT)



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FIGURE 72: CONSUMER SMART METER INSTANTANEOUS VALUES AFTER AN ON DEMAND MEASUREMENTS REQUEST

FIGURE 73: SCHEDULED WORK INDICATION (“SCHEDULE” TEXT)



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FIGURE 74: CONSUMER SUPPLY POINT SYMBOL (FUSE BOX)

FIGURE 75: EXAMPLE OF AN INCIDENT REPORT PREPARED BY THE LV NMS REPORTING TOOLS



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MULTISERVICE PRIME SUBNETWORK: USE CASE 1 Annex II.

FIELD DEPLOYMENT

ANNEX II.1 UPGRID CABINET MODEL 1

Figure 76 shows the schematics and dimensions of the UPGRID portable cabinet that has been used for

the LV remote control over PRIME field test scenarios (use case 1).

FIGURE 76: PORTABLE CABINET TYPE 1 TO BE USED FOR UPGRID TESTING

ANNEX II.2 SIMULTANEOUS AMI AND IP OVER PRIME TRAFFIC

This field deployment and validation was done over a SS within the demonstrator area. This section

describes the tests performed over the selected location. Figure 77 shows the operation web page of

the AMI data concentrator to be used for AMI data sending while UPGRID IP over PRIME traffic is also

transmitted. This AMI data concentrator had nine smart meters installed and accessible, that will be

used for data reading. This was the initial status of the AMI data concentrator with the smart meters

accessible.

FIGURE 77: SCREENSHOT FROM THE AMI DATA CONCENTRATOR BEFORE THE TESTS



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The goal of this initial test plan is to evaluate the channel usage sharing the media between AMI data

and remote control data. These are the main steps executed during the test plan.

- GTPs in the portable cabinet are upgraded to the latest UPGRID functionality version available

at the moment (identified as 3.23.80.36937).

- GTPs are integrated and configured with correct addresses in the same Iberdrola Virtual Local

Area Network (VLAN) as the devices under test. In this case it will be an AMI data exchange

test so the selected VLAN should be the one being used by the AMI data concentrator in that

location.

- Disable the PLC PRIME base node internal to the AMI data concentrator and make the

configuration required so the GTP with master role in UPGRID portable cabinet takes the role

of base node of that AMI network.

- Connect UPGRID cabinet so remote access is ensured.

- Measure_1: Force AMI traffic and check that results are successful. First iteration is done

without IP over PRIME traffic in parallel.

- Please note that AMI traffic for this measure is forced uploading this xml cycle to the AMI data

concentrator.

<cycles>

<cycle name="PRIME_11901122160_TORREABANDOIBARRA2_2" period="1" immediate="true"

stop="2017/08/14 22:03">

<get obis="0-0:1.0.0.255" class="8" element="2"/>

<get obis="1-0:99.1.0.255" class="7" element="2"

selective_access="structure{structure{long_unsigned{8}octet_string{00 00 01

00 00 ff}integer{2}long_unsigned{0}}date_time{2017/03/27

00:00:00}date_time{2017/03/28 10:00:00}array{}}"/>

</cycle>

</cycles>

- Measure_2: Force IP over PRIME traffic and measure the maximum delay of ICMP traffic sent.

First iteration is done without AMI traffic in parallel.

- Measure_3: Force AMI and IP over PRIME traffic in parallel and compare the performance

with the two measurements taken with only a type of traffic each time.

Some screenshot capture during the field tests are shown next:

In Figure 78, once the test scenario is ready, smart meters are registered to UPGRID GTP configured

as base node, as described above. Instead of being registered directly to the AMI data concentrator,

that was the initial status mentioned at the beginning of this section.



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FIGURE 78: METERS REGISTERED TO THE UPGRID GTP ACTING AS BASE NODE (MASTER)

ZIV PRIME Manager monitoring tool is used to measure PRIME PLC topology and traffic of this

UPGRID GTP under test (see Figure 79).

FIGURE 79: ZIV PRIME MANAGER TOOL USED FOR GTP PRIME PLC DATA ANALYSIS

Measure_1: Force AMI traffic and check that results are successful. First iteration is done

without IP over PRIME traffic in parallel.



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The result of AMI readings is successful seeing the following captures and behaviour. Note

that in the capture shown below, ZIV0044410732 smart meter is read. The information

shows transmission and reception traffic from the AMI data concentrator to this s pecific

meter. Analysing Distribution Line Message Specification (DLMS) traffic exchanged the

meters of that SS are read successfully and their AMI measurements are being gathered by

the AMI data concentrator.

A capture example is shown next. It is obtained with ZIV PRIME Manager monitoring tool

connected to the AMI data concentrator. This capture option represents PRIME 4-32

convergence sublayer traffic, this is the PRIME convergence sublayer defined for DLMS AMI

traffic exchange.

[TX] 2017/03/28 10:31:56 3046.150896 - ZIV0044410732

00 | d0 18 30 00 00 00 04 c6 fb 72 6b 06 d4 8e 0c 68

10 | fb 7d b7 10 0b dc 67 df 21 f9

[RX] 2017/03/28 10:31:57 3046.736496 - ZIV0044410732

00 | d4 81 f0 30 00 00 00 04 2a 82 52 95 2e 8f 97 29

10 | 81 b3 44 89 0f 09 55 1a 7c 4d 4a dd 3f e2 31 96

20 | f8 34 58 85 3b 8a e8 13 8d c1 70 3b 50 51 d7 ab

30 | 3c 06 02 6d 82 1d c7 47 be db d2 15 69 48 69 3a

40 | 5b bf 11 19 a1 9f 34 c3 ac 7c 48 48 71 d7 6b a6

50 | 1a 42 f0 47 7d 8f bb 35 24 74 d8 21 be ef 27 e7

60 | 36 d8 48 a8 42 03 84 f5 b9 5f 3f 03 9e ad a7 d4

70 | 77 8d d6 4c 9b 2f 3d c5 a5 70 fe 5b 07 cb bb 66

80 | d0 0e f9 e5 c8 49 bd 04 6b 5e fa 22 52 06 0c da

90 | eb 3c b5 d0 42 f1 6d 32 a1 72 5c 02 89 27 52 b3

a0 | 0d 1d dc 1a 94 6a 78 2a 94 29 2a 94 45 4b 94 1c

b0 | ed f8 e2 7f 26 6f e2 1d 4e 04 38 17 60 e9 cf fe

c0 | 94 c1 a1 f4 42 e4 eb fc bb 7e ac 45 8d d0 40 a2

d0 | 23 e7 14 f3 02 28 33 ff 0f 83 4d 8e 1a a6 10 f4

e0 | b7 c1 69 24 9a 8b 25 5c c4 67 53 76 f8 f5 0b b9

f0 | 1d 9b 7f

[TX] 2017/03/28 10:31:57 3046.747184 - ZIV0044410732

00 | d0 18 30 00 00 00 05 b6 d4 c5 6a 77 88 9a 12 ca

10 | 56 ca 99 e1 33 b8 fa ce cd 33

…

Measure_2: Force IP over PRIME traffic and measure the maximum delay of ICMP traffic

sent. First iteration is done without AMI traffic in parallel. Answer time with IP over PRIME

traffic never exceeds 450 ms. A capture example is shown next.

PING 192.168.1.1 (192.168.1.1): 56 data bytes

64 bytes from 192.168.1.1: seq=1 ttl=64 time=444.450 ms



149 | 201













…

Measure_3: Force AMI and IP over PRIME traffic in parallel and compare the performance

with the two measurements taken with only a type of traffic each time. The results of AMI

readings during this test are also successful. IP over PRIME traffic with AMI traffic in parallel

maintains the same latency in general 450 ms with punctual packets arriving around 1.500

ms. In any case traffic exchange is successful and the concept is validated, both types of

traffic can coexist. A capture example is shown next:

PING 192.168.1.1 (192.168.1.1): 56 data bytes






















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64 by

tes from 192.168.1.1: seq=23 ttl=64 time=1233.530 ms

…

ANNEX II.3 REMOTE CONTROL TRAFFIC OVER PLC PRIME

The goal of this advanced test plan is to exchange control data with the RTU over this IP over PRIME

architecture.

Figure 80 shows some images taken during the field validation process at TORRE ABANDOIBARRA 2 SS.

FIGURE 80: IMAGES OF THE REMOTE CONTROL TRAFFIC TEST PERFORMED AT TORRE ABANDOIBARRA 2 SS

First of all, there are some addressing conditions and limitations that required a local SCADA system for

the testing. It was not possible to enable the access to the RTU through the UPGRID GTPs portable

cabinet from the remote operation SCADA system.

Therefore, Figure 81 shows the initial situation of the SS under test.



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FIGURE 81: INITIAL SETUP AT TORRE ABANDOIBARRA 2 SS BEFORE THE TESTING

And Figure 82 shows the architecture set for the test scenario required for UPGRID remote control

validation over PLC PRIME. Note that both GTPs represented in blue are the devices mounted inside the

UPGRID portable cabinet (see section 4.2.2.1).

FIGURE 82: REMOTE CONTROL TRAFFIC TEST SETUP AT TORRE ABANDOIBARRA 2 SS

Over the architecture described, these are the main steps executed during the test plan.

- GTPs in the portable cabinet are upgraded to an improved UPGRID functionality version

developed for this advanced testing (identified as 3.23.80.38260). This is considered the last



152 | 201

UPGRID GTP version and therefore is given a manufacturing number

4WF01650009_upgrid_RC1, as shown in the screenshot taken during the field testing.

FIGURE 83: FINAL UPGRID FIRMWARE VERSION FOR MULTISERVICE CAPABILITIES OVER GTP

- GTPs are integrated and configured with correct addresses in the same Iberdrola VLAN as the

devices under test. In this case it will be a RTU control data exchange test so the selected

VLAN should be the one being used by the RTU in that location. IP over PRIME functionality

developed for UPGRID project should be enabled.

FIGURE 84: UPGRID MASTER GTP CONFIGURATION, INTEGRATED INTO THE PORTABLE CABINET

- Disable the AMI data concentrator as this test section is oriented to control traffic only and

make the configuration required so the GTP with master role in UPGRID portable cabinet

takes the role of base node.

- Connect UPGRID cabinet so the local SCADA can access the RTU.

- First connect the local SCADA directly to the RTU to ensure the communication. Then connect

it as the architecture shown in the test setup for further measurements.

- Measure_1: Force IP over PRIME traffic with ICMP packets to make sure the channel is

established.

- Measure_2: Connect the local SCADA to the RTU through IP over PRIME. This would validate

UPGRID concept for remote control traffic exchange over PLC PRIME. 104 control traffic is



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starter although due to addressing limitation further exchange is rejected. Anyway,

bidirectional 104 traffic is exchanged and the concept is validated.

- Measure_3: Connect the local SCADA an RTU simulated in a second PC (WinPCPau test tool).

See below some captures examples taken during these field tests.

Measure_1: Force IP over PRIME traffic with ICMP packets to make sure the channel is established.

A capture example is shown next:

C:\Windows\system32>ping -t 10.159.162.250

Haciendo ping a 10.159.162.250 con 32 bytes de datos:

Respuesta desde 10.159.162.250: bytes=32 tiempo=227ms TTL=63











…





Estadísticas de ping para 10.159.162.250:

Paquetes: enviados = 208, recibidos = 208, perdidos = 0

(0% perdidos),

Tiempos aproximados de ida y vuelta en milisegundos:

Mínimo = 211ms, Máximo = 1809ms, Media = 292ms

Control-C

Measure_2 and_3: Connect the local SCADA to the RTU through IP over PRIME. This would validate

UPGRID concept for remote control traffic exchange over PLC PRIME.

These are some screenshots taken during the remote control data exchange over PLC PRIME. These

captures were taken from the Iberdrola’s personnel PC used for the local control SCADA system. This PC

was represented at the top right hand corner in Figure 82.



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FIGURE 85: REMOTE WEB CAPTURE OF THE SS UNDER TEST

FIGURE 86: IBERDROLA SPECTRUM CONFIGURATION CHANGE TO ALLOW LOCAL SCADA ACCESS

FIGURE 87: RTU SIMULATED IN A PC OVER WINPCPAW, INSTALLED ALSO AT THE SS UNDER TEST



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FIGURE 88: WIRESHARK CAPTURE OF 104 CONTROL TRAFFIC OVER IP OVER PLC PRIME



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MULTISERVICE PRIME SUBNETWORK: USE CASE 2 Annex III.

FIELD DEPLOYMENT

ANNEX III.1 UPGRID CABINET MODEL 2

Figure 89 shows the schematics and dimensions of the UPGRID portable cabinet that has been used for

simulating SS locations where the SS does not have enough GPRS/3G coverage to let the router establis h

a good connection with the AMI Head System (use case 2).

FIGURE 89: PORTABLE CABINET TYPE 2 TO BE USED FOR UPGRID TESTING

ANNEX III.2 IP OVER PRIME AS AN ALTERNATIVE TO A SS WITHOUT

REMOTE ACCESS

This field deployment and validation was done over a SS within the demonstrator area. This section

describes the tests performed over the selected location. Figure 90 shows the operation web page of

the AMI data concentrator to be used for simulating a SS without remote access. This AMI data

concentrator had 491 smart meters installed and accessible. This was the initial status of the AMI data

concentrator with the smart meters accessible.



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FIGURE 90: SCREENSHOT FROM THE AMI DATA CONCENTRATOR BEFORE THE TESTS

Figure 91 shows the test scenario to be validated in the field.

FIGURE 91: USE CASE 2 TESTS SETUP AT MIRIBILLA 6 SS REPRESENTING A SS WITHOUT WAN COVERAGE

These are the main steps executed during the test plan.

- GTPs in the portable cabinet are upgraded to an improved UPGRID functionality version

developed for this advanced testing (identified as 3.23.80.38260). This is considered the last

UPGRID GTP version and therefore is given a manufacturing number

4WF01650009_upgrid_RC1, as shown in the screenshot taken during the field testing.

- Install GTP cabinet in the SS next to the AMI data concentrator.

- Adapt the configuration so PRIME node of the AMI data concentrator is disabled and the

internal base node of the GTP in the SS acts as base node of the network instead.

- Confirm that the network converges with this new topology configured.

- Install the second GTP as another meter in the meter room selected for WAN access testing.



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- Confirm that this GTP is registered as service node (slave) to the GTP installed in the SS.

FIGURE 92: SCREENSHOT FROM THE GTP IN THE METER ROOM (SLAVE) REGISTERED TO THE GTP IN THE SS (MASTER)

- Adapt the configuration and routing of all the elements so IP over PRIME channel is ensured.

- Measurement_1: Remote access to the AMI data concentrator from the meter room where

the GTP with WAN access is installed. This is IP over PRIME traffic.

- Measurement_2: Remote access to the AMI data concentrator from the meter room where

the GTP with WAN access is installed while AMI reading data is exchanged. This means that IP

over PRIME traffic and AMI traffic are exchanged simultaneously.

- Measurement_3: Remote access to the GTP with WAN access installed in the meter room

from the AMI operation system at Iberdrola premises. This ensures the last step of WAN

remote accessibility.

- Measurement_4: Remote access to AMI data concentrator from the AMI operation system at

Iberdrola premises, being the first step the WAN connection to the GTP with WAN access

installed in the meter room. This measurement is not possible due to routing limitations in

Iberdrola field operation networks.

These are some pictures taken during the field validation process at MIRIBILLA 6 SS and the meter room

selected for WAN access to the GTP that is Gernikako Lorategia,3.



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FIGURE 93: USE CASE 2 TEST PERFORMED AT MIRIBILLA 6 SS

FIGURE 94: USE CASE 2 TEST ENABLING WAN ACCESS FROM THE METER ROOM OF GERNIKAKO LORATEGIA 3

See below some captures examples taken during these field tests.

Measure_1: Remote access to the AMI data concentrator from the meter room where the GTP with

WAN access is installed. This is IP over PRIME traffic. A capture example is shown next. Note that

the following web server images are uploaded at the meter room being the IP traffic exchanged

over PLC PRIME from the SS.

GTP installed at the meter

room enabling WAN access



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FIGURE 95: CONNECTION PROCESS TO THE AMI DATA CONCENTRATOR FROM THE METER ROOM

Measure_2: Remote access to the AMI data concentrator from the meter room where the GTP with

WAN access is installed while AMI reading data is exchanged. This means that IP over PRIME traffic

and AMI traffic are exchanged simultaneously. A capture example is shown next:

This latency test shows that access is possible although there are some packets that do not arrive to

the destiny. 13% of the packets in this scenario are lost.

C:\Windows\system32>ping -t 10.159.164.169

Haciendo ping a 10.159.164.169 con 32 bytes de datos:




Tiempo de espera agotado para esta solicitud.






…

Tiempo de espera agotado para esta solicitud.








Estadísticas de ping para 10.159.164.169:

Paquetes: enviados = 67, recibidos = 58, perdidos = 9

(13% perdidos),

Tiempos aproximados de ida y vuelta en milisegundos:



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Mínimo = 325ms, Máximo = 3775ms, Media = 1287ms

Measure_3: Remote access to the GTP with WAN access installed in the meter room from the AMI

operation system at Iberdrola premises. This ensures the last step of WAN remote accessibility. A

capture example is shown next:

FIGURE 96: SCREENSHOT FROM THE AMI OPERATION SYSTEM DURING THE GTP WAN ACCESS



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MANAGEABLE PRIME SUBNETWORK (SNMP Annex IV.

MONITORING) FIELD DEPLOYMENT RESULTS

The following figures present some examples of the PRIME SNMP web based tool. At first, the idea was

to perform the tests in 40 real data concentrator but, due to connectivity issues in 4 of them, finally only

data from 36 data concentrators had been collected. These 40 AMI data concentrators are installed in

40 SSs that feed, in total, some thousands of residential Consumers. The list of 40 data concentrators in

the demonstrator area is shown in Table 22:

TABLE 22: LIST OF SS INVOLVED IN THE FIELD TEST OF THE MANAGEABLE PRIME SUBNETWORK

SS Code Name Number of

Consumers

200007470 GOIKOETXEA-VILLABASO 128

200000750 COOPERA.IPARRAGIR-BI 220

200005490 FINAL PRIM 151

901121590 PRIM- DOLARETXE 158

200002180 PLAZA INDAUTXU-BI 226

200001220 TRAVESIA VERDEL 710

200000200 SINDICAL 232

200000391 FINAL SAN FRANCISCO 277

200001940 HERMANAS CARMELITAS 537

200006990 ETXEANDIA-BILBAO 280

200004520 BIZKARGI 503

200004790 LEDESMA LEKERIKA 194

200007070 CASERIO ARBOLAGANE 280

200000210 ALHONDIGA-URKI/IPARR 304

200000610 SANTIAGO-BILBAO 322

200004400 B. ETXANIZ M. OREJA 332

200007501 VIVIENDAS FONTAN 342

901120210 INDALECIO PRIETO 396

901122620 BENIDORM 143

901101370 VENECIANA 401

200007580 LANDABASO-BILBAO 408

200007400 IBARREKO 1-BI 411

200001110 CAMPA EL MUERTO 419

200000970 NUEVA AURORA 432

200001080 ADORATRICES 357

200002470 VIVIENDAS AGARRE 432

200001750 ARTABE VDA. 433

200007720 ETXEA 442

200001810 MEDIA LUNA 443

200007610 TORREMADARI.J.CRUZ 448

200002720 CAMINO TUTULU 550

200003480 E.C.POZA 55 157

200003520 COCHERITO DE BILBAO 516

200003820 SANTA MARTA 2 324

200004570 ARABELLA II 345

200004880 TR.VERDEL-TR.CARMELO 537

200004910 F. DEL CAMPO-BI 363

200007080 BADAJOZ-L.GOIKOETXEA 243

901120060 MIRIBILLA 6-BILBAO 487

901121130 CONVENTO CONCEPCION 119



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Showing up next, the results from the tool with the graphics of the number of terminals (green lines)

and switches (blue lines) in each data concentrator installed in the SS listed in Table 22.

FIGURE 97: REAL DATA CONCENTRATOR A: TERMINALS AND SWITCHES

In the data concentrator shown in Figure 98 it is possible to notice that this network has an issue about

4:00 in the morning because, at that time, all the smart meters are disconnected. This issue can be

induced by the existence of either a particular noise or the data concentrator is rebooting periodically

due to some software issue. Usually, this periodic behaviour is caused by signal to noise in the network.

With this tool, these noises are easily identified and monitored, to implement solutions.

FIGURE 98: REAL DATA CONCENTRATOR B: TERMINALS AND SWITCHES



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FIGURE 99: REAL DATA CONCENTRATOR C: TERMINALS AND SWITCHES

In Figure 100, a smart meters drop is shown; this drop is due to the periodical reboot configured in all

the data concentrators. This reboot is configured to make it happen once a week in order to avoid any

kind of software issues on the device.

FIGURE 100: REAL DATA CONCENTRATOR D: TERMINALS AND SWITCHES



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FIGURE 101: REAL DATA CONCENTRATOR E: TERMINALS AND SWITCHES

FIGURE 102: REAL DATA CONCENTRATOR F: TERMINALS AND SWITCHES



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FIGURE 103: REAL DATA CONCENTRATOR G: TERMINALS AND SWITCHES

FIGURE 104: REAL DATA CONCENTRATOR H: TERMINALS AND SWITCHES



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FIGURE 70: REAL DATA CONCENTRATOR I: TERMINALS AND SWITCHES

FIGURE 105: REAL DATA CONCENTRATOR J: TERMINALS AND SWITCHES



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FIGURE 106: REAL DATA CONCENTRATOR K: TERMINALS AND SWITCHES

FIGURE 107: REAL DATA CONCENTRATOR L: TERMINALS AND SWITCHES



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FIGURE 108: REAL DATA CONCENTRATOR M: TERMINALS AND SWITCHES

FIGURE 109: REAL DATA CONCENTRATOR N: TERMINALS AND SWITCHES



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In Figure 110, a periodical drop of about 200 smart meters is shown. This drop is caused by noises in the

network but as it only affects to some smart meters, this noise has to be located in a concrete loc ation,

it can be a specific LV feeder or in a specific FB.

FIGURE 110: REAL DATA CONCENTRATOR O: TERMINALS AND SWITCHES

FIGURE 111: REAL DATA CONCENTRATOR P: TERMINALS AND SWITCHES



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FIGURE 112: REAL DATA CONCENTRATOR Q: TERMINALS AND SWITCHES

FIGURE 113: REAL DATA CONCENTRATOR R: TERMINALS AND SWITCHES



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FIGURE 114: REAL DATA CONCENTRATOR S: TERMINALS AND SWITCHES

FIGURE 115: REAL DATA CONCENTRATOR T: TERMINALS AND SWITCHES



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FIGURE 116: REAL DATA CONCENTRATOR U: TERMINALS AND SWITCHES

FIGURE 117: REAL DATA CONCENTRATOR V: TERMINALS AND SWITCHES



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FIGURE 118: REAL DATA CONCENTRATOR W: TERMINALS AND SWITCHES

FIGURE 119: REAL DATA CONCENTRATOR X: TERMINALS AND SWITCHES



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FIGURE 120: REAL DATA CONCENTRATOR Y: TERMINALS AND SWITCHES

FIGURE 121: REAL DATA CONCENTRATOR Z: TERMINALS AND SWITCHES



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FIGURE 122: REAL DATA CONCENTRATOR AA: TERMINALS AND SWITCHES

FIGURE 123: REAL DATA CONCENTRATOR AB: TERMINALS AND SWITCHES



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FIGURE 124: REAL DATA CONCENTRATOR AC: TERMINALS AND SWITCHES

FIGURE 125: REAL DATA CONCENTRATOR AD: TERMINALS AND SWITCHES



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FIGURE 126: REAL DATA CONCENTRATOR AE: TERMINALS AND SWITCHES

FIGURE 127: REAL DATA CONCENTRATOR AF: TERMINALS AND SWITCHES



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FIGURE 128: REAL DATA CONCENTRATOR AG: TERMINALS AND SWITCHES

FIGURE 129: REAL DATA CONCENTRATOR AH: TERMINALS AND SWITCHES



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REAL DATA CONCENTRATOR AI: TERMINALS AND SWITCHES

FIGURE 97: REAL DATA CONCENTRATOR AJ: TERMINALS AND SWITCHES



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MANAGEABLE PRIME SUBNETWORK (SNMP Annex V.

MONITORING) DETAILED EXAMPLE – SS 200000750

For this example a SS with two distribution transformers has been chosen. The location of the SS is

shown in Figure 130 below.

FIGURE 130: LOCATION FOR THE SS AND THE DATA CONCENTRATOR

This SS has one distribution transformer and gives service to 220 different Consumers. It has 7 LV

feeders and 2 LV switchboards. Figure 131 shows the LV switchboards.

FIGURE 131: THE TWO LV SWITCHBOARD OF THE SELECTED SS



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Figure 132 shows the data concentrator and the cabinet where it is installed in the selected SS.

FIGURE 132: DATA CONCENTRATOR

The steps to start a new data collection are as follow:

- First, the data concentrator had been upgraded and configured in order to enable its PRIME

advanced SNMP monitoring capabilities. The SNMP part of the data concentrator was

configured as follows:

FIGURE 133: SNMP CONFIGURATION IN DATA CONCENTRATOR

- Then, it was necessary to provision the data concentrator in the PRIME Management tool.



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FIGURE 134: PROVISIONING OF THE NODE IN THE WEB TOOL

FIGURE 135: PROVISIONED NODE

- Once the node was provisioned, two scheduling tasks were configured as explained in section

4.3. These two tasks were the recollection of the number of Terminals and the number of

Switches in the network.

- After 4 days, the collected data show the quality of the PRIME network ensuring the

communication during the test with all the meters. As it is shown, the number of smart meters

is around 200 (in green in the graphic) and the number of switches varies between 40 and 50

(in blue). It is important to remember that the switches are the service nodes acting as

repeaters for other service nodes in the network.

FIGURE 136: QUALITY OF PRIME NETWORK DATA STORED IN WEB TOOL AFTER 4 DAYS



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SMART METER ANALYSIS AND PROCESSING: Annex VI.

MACROS TOOLS

The following figures (Figure 137 to Figure 138) present some examples of results representation

obtained after executing the macro tools developed by Tecnalia for smart meter event analysis.

FIGURE 137: MAIN SHEET OF ONE OF THE DEVELOPED MACROS. IT CONTAINS THE EXECUTION CONFIGURATION

PARAMETERS (LEFT) AND THE SUMMARY OF RESULTS (RIGHT)

FIGURE 138: EXTRACT OF THE EXCEL TABLE RESULTED FROM EXECUTING THE MACRO THAT ANALYSES THE TIME OUT OF

VOLTAGE LIMITS AT FB LEVEL



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SMART METER ANALYSIS AND PROCESSING: Annex VII.

VIRTUAL REGISTER RESULTS

These annex provides with more examples of voltage magnitude issues at supply points analysed with

the Virtual Register (see Table 18).

ANNEX VII.1 MEASUREMENTS FROM SS_1 (UNDERVOLTAGE)

The information of the first SS (SS_1) at Table 23 is included next. There are 2 FBs in the SS_1, which is

within the worst undervoltage cases:



The code of smart meters belonging to each FB is shown in Table 18, while the graphical representation

obtained with the Virtual Register (Figure 139 - Figure 141) show that all these smart meters have

several measurements under the regulatory voltage (i.e. measurements are below the red line indicated

in the plots that indicates the regulatory voltage limit).

TABLE 23: SS_1 - METERS FROM WORST FB UNDERVOLTAGE


SS_1 FB_1 ZIV********44

SS_1 FB_1 ZIV********45

SS_1 FB_1 ZIV********49

SS_1 FB_1 ZIV********50

SS_1 FB_1 ZIV********51

SS_1 FB_1 ZIV********52

SS_1 FB_1 ZIV********53

SS_1 FB_1 ZIV********25

SS_1 FB_1 ZIV********27

SS_1 FB_1 ZIV********51

SS_1 FB_1 ZIV********22

SS_1 FB_2 ZIV********34

SS_1 FB_2 ZIV********36

SS_1 FB_2 ZIV********37



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187 | 201




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FIGURE 141: MEASUREMENTS FROM FB_2


There is only one FB in this SS classified as one of the worst undervoltage cases: FB_3. It has 11 smart

meters and their codes are shown in Table 24, while the following figures show that all these meters

have several measurements under the regulatory voltage (indicated in the plots with a red line). Some

meters such as ZIV0041963449, ZIV0041963634, ZIV0041963636, ZIV0041963638 and ZIV0043100833

have recorded fewer measurements than the average gathered by the Virtual Register. As they do not

provide useful information, their plots have not been included in this deliverable.

TABLE 24: SS_2 SMART METERS FROM WORST FB (UNDERVOLTAGE)

SS_NAME FB_CODE METER CODE SS_2 FB_3 ZIV********12

SS_2 FB_3 ZIV********44

SS_2 FB_3 ZIV********47

SS_2 FB_3 ZIV********49

SS_2 FB_3 ZIV********50

SS_2 FB_3 ZIV********52

SS_2 FB_3 ZIV********34

SS_2 FB_3 ZIV********36

SS_2 FB_3 ZIV********38

SS_2 FB_3 ZIV********96

SS_2 FB_3 ZIV********33



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The FB_4, belonging to SS_3 is classified as one of the worst undervoltage cases. It has 10 smart meters,

which are shown in Table 25 while the following figures show that all these meters have several

measurements under the regulatory voltage (indicated in the plots with a red line).

TABLE 25: SS_3 - METERS FROM WORST FB (UNDERVOLTAGE)

SS_NAME FB_CODE METER CODE SS_3 FB_4 ZIV********31 SS_3 FB_4 ZIV********35

SS_3 FB_4 ZIV********80

SS_3 FB_4 ZIV********87

SS_3 FB_4 ZIV********32



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SS_3 FB_4 ZIV********36

SS_3 FB_4 ZIV********37

SS_3 FB_4 ZIV********90

SS_3 FB_4 ZIV********95 SS_3 FB_4 ZIV********31

FIGURE 143: MEASUREMENTS FROM FB _4 (PART 1)



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There are 2 FBs in this SS within the worst undervoltage cases:

FB_5, with 5 smart meters


The code of meters belonging to each FB is shown in the table, while the following figures show that all

these meters have several measurements under the regulatory voltage (indicated in the plots with a red

line). These measurements have been gathered through the Virtual Register tool .

TABLE 26: SS_4 METERS FROM WORST FB (UNDERVOLTAGE)


SS_4 FB_5 ZIV********00

SS_4 FB_5 ZIV********25

SS_4 FB_5 ZIV********91 SS_4 FB_5 ZIV********55

SS_4 FB_5 ZIV********60

SS_4 FB_6 GE*********42

SS_4 FB_6 GE*********89 SS_4 FB_6 GE*********74

SS_4 FB_6 GE*********55 SS_4 FB_6 GE*********70

SS_4 FB_6 GE*********20

SS_4 FB_6 LG*********57

SS_4 FB_6 ZIV********24



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193 | 201





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There are 4 FBs in this SS within the worst undervoltage cases:



FB_8, with 1 smart meter

FB_10, with 1 smart meter


these smart meters have several measurements, gathered through the Virtual Register tool, under the

regulatory voltage (indicated in the plots with a red line).

TABLE 27: SS_5 - METERS FROM WORST FB (UNDERVOLTAGE)


SS_5 FB_7 ZIV********28

SS_5 FB_9 ZIV********24

SS_5 FB_9 ZIV********29

SS_5 FB_8 ZIV********17 SS_5 FB_10 ZIV********63





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ANNEX VII.6 MEASUREMENTS FROM SS_6 (OVERVOLTAGE)

There are 2 FBs in this SS within the worst overvoltage cases:




these meters have some measurements over the regulatory voltage (indicated in the plots with a red

line).

TABLE 28: SS_6 SS - METERS FROM WORST FB (OVERVOLTAGE)


SS_6 FB_11 ZIV********43



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SS_6 FB_11 ZIV********81

SS_6 FB_11 ZIV********02

SS_6 FB_11 ZIV********52

SS_6 FB_11 ZIV********56

SS_6 FB_11 ZIV********48

SS_6 FB_12 ZIV********92

SS_6 FB_12 ZIV********09

SS_6 FB_12 ZIV********35




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There is one FB in this SS belonging to worst overvoltage cases: FB_13. The code of its ten smart meters

is shown in the table. Besides, the following figures show that none of these meters have any

measurements over the regulatory voltage (indicated in the plots with a red line).It is also remarkable

that a number of measurements is missed along the same periods in these meters. It may be attributed

to the billing process during the nights.

TABLE 29 SS_7 SS - METERS FROM WORST FB (OVERVOLTAGE)


SS_7 FB_13 ZIV********97

SS_7 FB_13 ZIV********59

SS_7 FB_13 ZIV********73

SS_7 FB_13 ZIV********58

SS_7 FB_13 ZIV********63

SS_7 FB_13 ZIV********12

SS_7 FB_13 ZIV********97

SS_7 FB_13 ZIV********48

SS_7 FB_13 ZIV********30




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There is one FB in this SS belonging to worst overvoltage cases: FB_14. It has three meters, whose code

is shown in the following table.

TABLE 30 SS_8 - METERS FROM WORST FB (OVERVOLTAGE)

SS_NAME FB_CODE METER CODE SS_8 FB_14 SAG********50

SS_8 FB_14 ZIV********58

SS_8 FB_14 ZIV********59

Besides, the following figures show these meters have only a few measurements over the regulatory

voltage (indicated in the plots with a red line).



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There is one FB in this SS belonging to worst overvoltage cases: FB_15. The code of its five meters is

shown in the table below.

TABLE 31 SS_9- METERS FROM WORST FB (OVERVOLTAGE)


SS_9 FB_15 ZIV********03

SS_9 FB_15 ZIV********24

SS_9 FB_15 ZIV********94

SS_9 FB_15 ZIV********95

Besides, the following figures show that none of these five smart meters have any measurements over

the regulatory voltage (indicated in the plots with a red line).



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demonstration results: evaluation and opportunities

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