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DIMMER
D1.3.2 – Data collection: type, format and methodology 1
Small or medium-scale focused research project (STREP)
FP7-SMARTCITIES-2013
ICT-2013.6.4 Optimizing Energy Systems in Smart Cities
District Information Modeling and Management
for Energy Reduction
DIMMER
Project Duration: 2013.10.01 – 2016.09.30
Grant Agreement number: 609084
Collaborative Project
WP1 Polito
D1.3.2 Data collection: type, format and
methodology
Prepared by DIMMER Collaboration Submission date 30.09.2014 Due date 30.09.2014 Nature of the deliverable R P D O
Dissemination level PU PP RE CO
Project Coordinator: Prof. Enrico Macii, Politecnico di Torino
Tel: +39 011 564 7074
Fax: +39 011 564 7090
E mail: [email protected]
Project website address: http://dimmer.polito.it
DIMMER
D1.3.2 – Data collection: type, format and methodology 2
REVISION HISTORY
Date Version Author/Contributor1 Comments
2014.08.20 V01 Polito Initial Structure for comment
2014.09.15 V02 Polito Contribution
2014.09.15 V03 STP Contribution
2014.09.15 V04 UNIMAN Contribution
2014.09.25 V05 Arup Contribution
2014.10.01 V06 ISMB Review
2014.10.02 V07 Polito Final
1 Partner, Name Surname
DIMMER
D1.3.2 – Data collection: type, format and methodology 3
COPYRIGHT
This project has received funding from the European Union’s Seventh Framework Programme for research, technological
development and demonstration under grant agreement n° 609084.
© Copyright 2013 DIMMER Consortium consisting of
This document may not be copied, reproduced, or modified in whole or in part for any purpose without written
permission from the DIMMER Consortium. In addition to such written permission to copy, reproduce, or modify this
document in whole or part, an acknowledgement of the authors of the document and all applicable portions of the
copyright notice must be clearly referenced.
All rights reserved.
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D1.3.2 – Data collection: type, format and methodology 4
TABLE OF CONTENTS
Revision History .............................................................................................................................. 2
Copyright ........................................................................................................................................ 3
Table of Contents ............................................................................................................................ 4
List of Figures .................................................................................................................................. 5
List of Tables ................................................................................................................................... 5
LV Abbreviations ............................................................................................................................. 6
Executive summary ......................................................................................................................... 7
Introduction .................................................................................................................................... 8
1. Measurements in the Turin District ........................................................................................... 9
1.1. Measured quantities ................................................................................................................................................ 9
1.2. Measurement methodology .................................................................................................................................... 9
1.3. Data format ............................................................................................................................................................ 11
2. Measurements in the Manchester District .............................................................................. 12
2.1. Coherent energy monitoring system ..................................................................................................................... 12
2.2. OSI-Soft energy monitoring system ....................................................................................................................... 13
2.3. Energy Dashboard .................................................................................................................................................. 14
2.4. Application of the data measurements .................................................................................................................. 15
3. Conclusions ............................................................................................................................ 18
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D1.3.2 – Data collection: type, format and methodology 5
LIST OF FIGURES
Figure 1 – An hypothetical sensor distribution inside one of the selected buildings within the Turin demonstrator, according
to the rooms orientation and exposition within a floor type. .................................................................................................. 10
Figure 2 – Screenshots of the web portal. ................................................................................................................................ 12
Figure 3 – Architecture of the system and the API link between the system and DIMMER. .................................................... 13
Figure 4 – Screenshot of the Dashboard. ................................................................................................................................. 15
Figure 5 – A schematic of the interaction of the electrical, heat and gas networks at the district level. ................................ 17
LIST OF TABLES
Table 1 – List of measurements for each substation/building ................................................................................................... 9
Table 2 – List of measurements on the district heating network ............................................................................................... 9
Table 3 –OSI-Soft energy monitoring system ........................................................................................................................... 14
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D1.3.2 – Data collection: type, format and methodology 6
LV ABBREVIATIONS
Acronym/Symbols Full name
API Application Programming Interface
GIS
MV/LV
Geographic Information System
Medium voltage/Low voltage
SQL Standard language for accessing databases
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D1.3.2 – Data collection: type, format and methodology 7
EXECUTIVE SUMMARY
The measurement system is a crucial part of the DIMMER approach. This document describes the quantities that are
measured in the two districts, the format of the data and the measurement methodology.
The two districts differ in terms of type of data that are measured and detail of the analysis. In the Turin district, the only
energy driver is heat distributed through the district heating network. In the Manchester districts, multiple energy vectors
are distributed through networks: gas, electricity and heat. The analysis is performed at building level in the Turin district
and at an integrated level in the Manchester district. These differences highlight the flexibility and the application
capabilities of the DIMMER strategy.
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D1.3.2 – Data collection: type, format and methodology 8
INTRODUCTION
Both the development and the implementation of the DIMMER project are based on measurements of quantities that
allow one to characterize energy consumption and comfort conditions. The measurement system in the two districts
consists of sensors, mostly of which were previously installed. The system to collect measurements at district level,
therefore the additional sensors that are currently under installation should be compatible with the existing system.
A description of the measurement system in the Turin district and the way the various measurements can be used in order
to set the DIMMER system is available in the deliverable D1.3.1. Data acquisition in the Manchester district was not fully
discussed because of additional difficulties, therefore a description is provided here.
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D1.3.2 – Data collection: type, format and methodology 9
1. MEASUREMENTS IN THE TURIN DISTRICT
1.1.Measured quantities
As described in the deliverable D1.3.1, the implementation of the DIMMER strategies in the Turin district heating system
requires measurements in the involved buildings and on the network. Measurements in the buildings are performed in all
the substations, i.e. the interconnection between the buildings and the network, but also in some of the rooms. A
complete list of the measurements considered at the current stage of the DIMMER project is available in Tables 1 and 2.
Table 1 – List of measurements for each substation/building
Table 2 – List of measurements on the district heating network
1.2.Measurement methodology
As discussed in the D1.1, before the beginning of the DIMMER project, three temperatures were measured in the heat
exchangers located in the buildings: the supply and return temperatures on the network side and the supply temperature
on the building side. An additional sensor for the measurement of the return flow temperature on the building network
side of the heat exchangers is under installation (These are the sensors indicated as B71 and B32 sensor in the Siemens
manual). The sensors, as indicated by the controller vendors, that should be installed are the strap-on QAD22 sensor for
Siemens controller and the EMSxxx for Danfoss ECL regulator. Measurements will be performed each 6 minutes.
Some of the buildings will be equipped with several temperature and relative humidity sensors in various parts of their
volumes in order to precisely map the house temperature distribution . Some buildings have already been identified (see
Figure 1 for details) but the idea is to define a wider range of “reference buildings” that could cover a large number of
existing typologies of building, in terms of construction categories and expected uses. Sensors definition and installation
Water mass flow rate supplied by the district heating network (secondary network)
Temperature of water entering the heat exchanger on the secondary network
Temperature of water exiting the heat exchanger on the secondary network
Temperature of water exiting the heat exchanger on the user network
Temperature of water entering the heat exchanger on the user network
External temperature
Pump running status
Selected climatic curve
Internal temperatures in the building in rooms located on the top floor
Indoor temperature and relative humidity in the selected rooms representative of the
building type
Mass flow rate entering the heat exchanger of each thermal plant and storage tank
Temperature of water entering the heat exchanger of each thermal plant and storage tank
Temperature of water exiting the heat exchanger of each thermal plant and storage tank
Mass flow rate entering each pumping station or booster pumping station
Pressure of water entering each pumping station or booster pumping station
Pressure of water exiting each pumping station or booster pumping station
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D1.3.2 – Data collection: type, format and methodology 10
will be the core of task T1.2, but it is already possible to evaluate some basic features. For example has been early
considered the future deployment of wireless sensors, and/or portable ones, in order to preliminary evaluate the correct
and most representative places in the buildings to install them and, even more, the possibility to subsequently place them
in different sites in order to cover a wider range of buildings with the same amount of sensors. At present some
hypothesis on the rooms representative of the building type have been carried out, taking into account some parameters
such as orientation, exposition, room volume, horizontal distribution and – for the selected multi-storey buildings – the
floor level (in order to assess the influence of the vertical distribution of temperatures on energy consumption). The idea
is to identify the reference building’s thermal behavior in order to extend the results to other existing building typologies
in terms of construction categories and expected uses.
Figure 1 – A hypothetical sensor distribution inside one of the selected buildings within the Turin demonstrator, according to the rooms’
orientation and exposition within a floor type.
There are several different methods and technologies to measure temperatures in buildings, rooms etc. The aim of the
measurement system that is proposed in the DIMMER project is to interconnect building and room sensors to the district
heating network control system in order to improve the regulation mechanism and the analysis capabilities, by gathering
all available data (heat exchangers, heat controller and building and rooms’ temperatures) at the same time. It will be
possible to integrate in the LinkSmart infrastructure data coming from different sources, e.g., from an ad-hoc sensor
platform developed by ST-Polito and from devices available from the market and employed by IREN ENERGIA (Task 2.1
and T2.2).
For indoor data collection, STP is developing an ultra-low power wireless sensor network platform able to integrate
different kind of sensors (temperature and humidity for the specific aims of the Project, but also atmospheric pressure,
vibrations, etc.) and to send data to a central collector (or gateway) visible by the LinkSmart middleware infrastructure.
The sensor nodes will be battery-operated and extremely easy to setup, with no specific location requirements, and will
transmit data using Sub-GHz radio transceivers. More in details, a mesh network architecture is used, where each node is
able to acquire environmental data, to send them towards the gateway and to contribute to the transmission and routing
of data coming from other nodes. The complete system will be active and synchronized only when data sampling and
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D1.3.2 – Data collection: type, format and methodology 11
transmission is required (e.g., 10 seconds every 15 minutes), and will turn to a low-power state for the rest of the time,
thus increasing battery lifetime. The gateway will be implemented as any Internet-connected PC (or netbook) running the
LinkSmart middleware and equipped with a dedicated USB radio transceiver, or possibly a dedicated router.
Outside temperature sensors are already installed in every building and connected to the heat controller. Each building is
equipped with a smart gateway box, provided by IREN ENERGIA, that retrieves data from the heat meter and the heat
controller and transmits all data in real time to the servers. Using smart gateway’s auxiliary communication ports, it is
possible to connect other devices to the gateway, such as temperature sensors, PLC, meter controller and others; wireless
gateways will be installed so that to retrieve data from wireless sensors. These devices recently became very popular and
easy to install, because they are equipped with tiny solar cells and they don’t need wires and cables. In particular, 868Mhz
EnOcean sensors will be installed.
In order to reduce the risk of communication problems, it will be taken into account the possibility to install new
temperature sensors based on 169Mhz frequency range and on new M2M low power CPU; these technologies have been
recently made available on the market.
For each building equipped with a remote controlled thermal substation it will be possible to gather 5-minute
consumptions and operation data, together with external temperature coming from the substation specific weather
station.
1.3.Data format
The indoor sensor network platform devised by STP will be integrated in the DIMMER infrastructure through the
LinkSmart middleware. The preliminary implementation will periodically share data from the sensor network through the
gateway in a very simple textual packet format on a virtual serial connection, as in the following format:
[NODE_ID; YYYY-MM-DD; HH:MM:SS; T=xxxxx; H=xxxxx],
where each field represents, respectively, the identification code of the node acquiring data from the environment,
acquisition date and time, temperature (in degrees) and relative humidity values. The actual format is being discussed
within the Project consortium.
Further development of the communication protocol will consider a bidirectional communication, in order to enable the
user to interact with devices to configure network behavior and acquisition parameters.
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D1.3.2 – Data collection: type, format and methodology 12
2. MEASUREMENTS IN THE MANCHESTER DISTRICT
2.1.Coherent energy monitoring system
The University of Manchester’s data network integrates utility metering (natural gas, heat, electricity and water).
This system (installed and maintained by ‘Coherent Research’) presents consumption data aggregated into 30-minute
intervals. Data are presented on a web-based system as charts for chosen date ranges, or can be downloaded as CSV files.
Fiscal meters (used for transactions with the energy suppliers), sub-metering, and virtual meters (additions of numerous
sub-meters) are presented on the web portal. Screenshots are shown in Figure 2.
Figure 2 – Screenshots of the web portal.
It is envisaged that the data from the Coherent system will be available for the DIMMER project, and figure 3 presents the
architecture of the system and the API link between the system and DIMMER.
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D1.3.2 – Data collection: type, format and methodology 13
Figure 3 – Architecture of the system and the API link between the system and DIMMER.
2.2.OSI-Soft energy monitoring system
As part of a developing initiative further monitoring is being installed on one Medium Voltage ring main comprising 18
MV/LV transformers. These have been fitted with Ethernet/broadband over power-line connections. This allows for high
resolution monitoring and recording of network behavior in terms of voltage, current, frequency and power characteristics
at high definition, typically at one second intervals.
This ‘OSI-Soft’ system is a high granularity data capture and analysis research initiative covering the following University
district ring main and buildings.
Data Collection
Service (DCS)
Windows Server
SQL Server with
DCS schema
definition
Web
Application
(DCS WebAPP)
Web Service
interface (DCS
WebService)
Configuration
& view data
Communication
DIMMER Envisaged
DIMMER API
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D1.3.2 – Data collection: type, format and methodology 14
Table 3 –OSI-Soft energy monitoring system
Buildings Ring main line diagram
- Manchester Museum
- Arthur Lewis
- Manchester business School (MBS) plus their
new hotel when built
- HBS
- NWCP (car park)
- Bridgeford Street
- Rear Quad
- John Rylands University Library (JRUL)
- Sam Alexander
- Ellen Wilkinson
- AFLC
- Centrifuge
2.3.Energy Dashboard
The Dimmer Dashboard is a web-based application which utilises the latest technology in data visualisation, web-mapping
and real-time 3D to enable the user to inspect, analyse, and manage energy consumption data from the University of
Manchester’s (UoM) energy monitoring systems.
The dashboard takes data from the UoM’s system via a SOAP2 web-service and stores the consumption data in a relational
database. This data is then integrated with spatial data from the project GIS and 3D Model and used by the dashboard
front end to create interactive data visualisations.
The front-end user interface consists of three elements:
• Interactive Charts and Graphs. These are generated using the Crossfilter and Dimensional charts APIs which
enable the production of interlinked charts and data visualisations which make use of dynamic multi-dimensional
queries of large datasets. When the user manipulates a chart or graph (e.g. using a zoom feature), the other
linked charts and visualisations are automatically filtered. This enables the user to examine multiple scenarios
and to drill down into the dataset to understand the relationships between different aspects of the data.
2 Simple Object Access Protocol
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D1.3.2 – Data collection: type, format and methodology 15
• Web-GIS. Using the leaflet web-mapping API, this is an interactive map which allows the user to view buildings
and other district features within their real-world spatial setting. It also allows the user to access attributes and
data related to the features and represents the energy consumption in symbolic form on the map
• Realtime 3D. The realtime 3D model uses the Unity 3D software to generate a web-viewable 3D model of the
district. This shows fully rendered buildings and features in 3D and allows the user to fly around the district and
inspect buildings and other features within an intuitive and realistic virtual model.
Together these three elements allow the user to inspect the underlying data using three unique entry points and
interfaces which provides the ability to visualise the data, and examine scenarios in an easy and intelligent manner. The
system also provides an extensible platform for the creation of future visualisations and applications using a simple API-
based approach which provides potential interoperability with other systems and applications where required.
The Dashboard is a work in progress, not yet complete; screen shots are presented below to illustrate the progress made
so far on this.
Figure 4 – Screenshot of the Dashboard.
2.4.Application of the data measurements
In terms of scoping down potential applications of the data being gathered in the Manchester demo, some of the work
carried out at the University of Manchester aims at developing an integrated energy network model that considers
simultaneously part of the electrical network, heat network and gas network of the considered district.
In fact, especially for technologies that are coupled electro-thermally (for instance, electric heat pumps (EHP) or combined
heat and power (CHP)), changes from both the operational and planning standpoints in one network can affect another
one within the district. Therefore, so as to properly explore both the implications and the potential benefits of certain
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D1.3.2 – Data collection: type, format and methodology 16
energy efficiency or control strategy carried out, it is necessary to model all the involved district energy networks in an
integrated fashion.
In order to carry out the above, the model requires various inputs:
• the topology and the characteristics of the three networks (for example, length of cables and pipes, electrical
impedances, size of heat and gas pipes, and so forth),
• information about the multi-energy consumption at each node of the networks, also corresponding to buildings
connections (for example, electricity and gas or electricity and heat, depending on specific node and building),
• information about the conversion technology characteristics that may be present at different nodes (for instance,
connection to the upstream electrical network, treated as the slack node in the electrical model; or the presence of a
gas boiler in another building).
In particular, the time series information from the COHERENT system will be used to populate the network nodal multi-
energy profiles for the monitored buildings.
The model then elaborates the relevant multi-energy network variables in a time series form (for instance, over 24 hours
with the relevant time resolution - half-hourly - available from the measurements) so as to “picture” the operational
network state in terms of voltages and power flows, gas flow rates and nodal pressures, hot water mass flow rates and
temperatures, electrical and thermal losses, and so forth.
Specific studies that are planned to be run once the model is consolidated are:
• Multi-energy network flow analysis to “picture” the impact of different technology and energy efficiency intervention
scenarios on the electricity, heat, gas and in case water networks;
• From an operational perspective, to simulate for a given system and scenario different control policies, demand
response options, and active network management strategies, in the presence of network constraints, coordinated
change of temperature settings in buildings, etc;
• From a planning perspective, to study the impact on flows and need for network reinforcement for different
scenarios such as centralised CHP, centralised EHP, mixed CHP-EHP, decentralised EHP, etc.
The analyses will use as a primary test network a model of the Manchester demonstrator, based on COHERENT demand
data, as mentioned above, but will probably address other cases as well.
A schematic of the interaction of the electrical, heat and gas networks at the district level is shown in Figure 5. The
electricity and heat networks are linked through the conversion components (e.g., CHP units, EHP, electric boilers, and
circulation pumps). These conversion components allow flows of energy between the two networks: the CHP units
generate electricity and heat simultaneously; heat pumps and electric boilers convert electricity to heat; circulation pumps
consume electricity to circulate water in the district heating network. The gas networks then interacts on the supply side
with the electrical network through gas generators or CHP and with heat network through boiler or again CHP, while its
compressors are in turn powered by electricity.
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D1.3.2 – Data collection: type, format and methodology 17
Figure 5 – A schematic of the interaction of the electrical, heat and gas networks at the district level.
Heat pumps or
electric boilers
Gas
generators
Circulation pumps
Gas boilers
CHP Units
Compressors
District heating networks
Heat flow
Electrical networks
Gas networks
Gas flow
Electrical flow
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D1.3.2 – Data collection: type, format and methodology 18
3. CONCLUSIONS
With this deliverable, description of the measurements in the two districts, Turin and Manchester, is completed. The
DIMMER strategy is applied in the districts at two different levels. In Turin a single energy vector, heat distributed through
the district heating network, is considered. The analysis is performed at the detail of each single building and the strategy
is performed by acting on the thermal request profile of the buildings. The analysis is also performed considering some
temperatures inside the buildings to check that the thermal profiles do not have negative effects in the comfort conditions
of the users. In the Manchester districts, multiple energy vectors are examined: gas, electricity and heat. The DIMMER
strategy here is applied to the integrated system. A model is used in order to investigate possible improvements obtained
at operational level or planning level.