tran studyelectrical 2012a
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Transformer failure reportTRANSCRIPT
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Study of Electrical Usage and Demand at the
Container Terminal
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To Tam, Matthew and Chloe
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Acknowledgements
I am particularly indebted to my principal supervisor Professor Alfred Deakin
Professor Saeid Nahavandi for his constant guidance and support throughout this
PhD. I am very grateful for his insights, assistance, patience and support over the last
few years. This thesis would not be completed without his encouragement and
support.
I also would like to thank my associate supervisor Dr. Doug Creighton for the
valuable guidance and advice he provided me during the course of my PhD.
I would especially like to thank Robert Reid of Robert Reid and Associates, a mentor
and colleague who arranged for permissions to collect data at Melbourne container
terminals for this study. He also provided access to data of overseas container
terminals for validating the results.
I acknowledge Patrick Stevedores, P&O Ports, Hutchison Port Holdings and Maher
Terminal Holding Corp. for their assistance in providing the data.
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ABSTRACT
Modeling and simulation techniques are the tools to be used for optimizing the
operation and fully utilize access of a container terminal for a projected container
throughput. The container terminal operator uses these study results to make
decisions and planning for the redevelopment and/or expansion of the terminal.
Usually, a new terminal layout with new truck traffic and more container handling
machines is required to cope with the projected container throughput. It is then the
electrical engineers task to calculate the terminal maximum electrical load demand
and design the electrical infrastructure accordingly.
A container terminal is a specific engineering field and currently there is no standard
or guidance for electrical engineers to accurately calculate the maximum electrical
demand. This study of electrical usage and demand at the container terminal was a
practical approach to:
x addressing the problem of how to estimate/calculate the maximum electrical
demand of a container terminal with known number of electrical equipment
and
x contributing to the understanding of regenerative energy issue of container
handling cranes at the container terminal.
Operation and electrical data at a Melbourne container terminal were daily collected
for more than two (2) years for this study. Collected operation data was analysed
according to the number of containers, their weights and set temperature for
refrigerated containers (reefers). Container weights were used to calculate the
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electrical demand of the container handling cranes. Collected daily electrical data
was correlated to the number of reefers to determine the electrical demand of these
reefers. Maximum electrical demands of container handling cranes and reefers were
determined by analysing all calculated values over the whole data collection period.
Maximum electrical demand of the container terminal was then calculated by adding
the other loads at the terminal: office, lightings and workshop.
The maximum electrical demands of several container terminals in Australia, USA,
Canada and China were calculated using the results of this study and the other
method (the diversity factor method). These calculated maximum electrical demands
were compared with the actual electrical demands with pleasing results: whilst at
least 34% less than the value calculated using the other method, the electrical
demand calculated using the results of this study was indeed the MAXIMUM
DEMAND and still with ample spare capacity of at least 20% for the safety margin
and future expansion of the terminal.
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Tables of Contents Table of Contents iv
List of Abbreviations viii
List of Figures ix
List of Tables xiii
List of Formula xiv
1. Introduction 1
1.1 Background information 1
1.2. Research aims and objectives 4
1.3. Outline of the thesis 6
2. Literature Review 7
2.1 Overview Papers 7
2.2 Electrical Energy Usage and Demand Papers 9
2.3 Formula for Electrical Power calculation 11
3. Electrical Assets Identification and Set up Data Collection Scheme 19
3.1 Identification of electrical assets at container terminal 20
3.1.1 Processes at container terminal 20
3.1.2 Electrical assets at container terminal 26
3.2 Definition of Electrical Demand 28
3.2.1 Definition from the Utilities 28
3.2.2 Definition from Electricity Bills and measured energy 29
3.2.3 Definition from Digital Power Meters 32
3.3 Focusing study on average electrical demand 34
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3.3.1 Reasons for focusing study on average demand instead of peak
demand 35
3.3.2 Decision of focusing the study on average demand 36
3.4 Set up at Melbourne Container Terminal for collecting data 36
3.5 Conclusions 40
4. Container Handling Cranes 42
4.1 Brief Discussion of container handling cranes 43
4.2 Load Profiles of Quay Crane Comparison between AC and DC drive
systems 47
4.2.1 AC and DC quay cranes under study 48
4.2.2 Study results 49
4.2.3 Study conclusions 57
4.3 Container Weight Analysis 57
4.3.1 Weight of container container ship and ISO standard 57
4.3.2 Weight of container at Melbourne Container Terminal 60
4.3.3 Results of analysing data collection 63
4.3.4 Conclusions of weight analysis 63
4.4 Calculate Demand & Energy usage of container handling cranes 67
4.4.1 Quay Crane and Maximum Electrical Demand 67
4.4.2 RMG and ASC and maximum Electrical Demand 70
4.5 Conclusions 72
5. Refrigerated Container 74
5.1 Brief Description of Refrigerated Container 74
5.2 Estimate Electrical Demand of Refrigerated Container 76
5.2.1 Maximum Demand of a Reefer Stack 77
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5.2.1.1 Demand calculation using Australian Standard AS3000 77
5.2.1.2 Demand calculation using diversity factor 80
5.2.1.3 Other demand calculation method 81
5.2.1.4 Reefer demand information from Container Handbook 82
5.2.1.5 Demand calculation based on heat transfer & required cooling 83
5.3 Measure the actual reefer electrical demand 88
5.3.1 Description 88
5.3.2 Data collection and analysing 89
5.3.3 Results of analysing data collection 95
5.4 Comparison of maximum demand calculated by different methods 104
5.5 Conclusions 108
6. Reducing electrical maximum demand and energy usage 109
6.1 Reducing electrical maximum demand 109
6.1.1 Improving power factor to reduce maximum demand 109
6.1.2 Using cranes with DC drive system to reduce maximum
Demand 112
6.2 Reducing electrical energy usage 113
6.2.1 Using cranes with DC drive system to reduce energy usage 113
6.2.2 Utilisation of the regenerative energy to reduce energy usage 114
6.2.3 Reduce energy usage by lighting 123
6.2.4 Energy Storage and Peak Lopping 126
6.3 Conclusions 130
7. Verification of this study results 131
7.1 Calculation of the maximum demand at container terminal 132
7.1.1 Calculation to AS/NZS 3000:2007 133
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7.1.2 Calculation using diversity factors 134
7.1.3 Calculation using findings of this study 135
7.2 Maximum demand at Container Terminals 136
7.3 Comparison of the results 140
7.4 Conclusions 149
8. Conclusions and directions for future research 150
8.1 Conclusions 151
8.2 Directions for future research 153
Appendix
Appendix A Daily Container Report, Code of Excel macro & Results 155
Appendix B Daily Reefer Report, Code of Excel macro & Results 161
Appendix C Specific Heat Capacity of various Products 173
Appendix D Calculated Reefer Electrical Demand using Heat transfer and
Cooling require Method 174
Appendix E Data Volume 183
References 184
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List of Abbreviations
AC Alternating Current
AGV Automatic Guided Vehicle
ASC Automatic Stacking Crane
DC Direct Current
ESCAP Social Commission for Asia and the Pacific
EMS Energy Management System
RMG Rail Mounted Gantry
RTG Rubber Tyred Gantry
QC Quay Crane
SC Straddle Carrier
STS Ship to Shore Crane
SWL Safe Working Load
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List of Figures
3.1 Stowage plan of a container ship
20
3.2 Quay cranes
21
3.2 Straddle Carrier
21
3.4 Container ship unloading plan
21
3.5 Melbourne Container Terminal storage stack
22
3.6 Straddle Carrier deliver container to truck
23
3.7 Container ship loading
24
3.8 Processes at Container Terminal
25
3.9 Port Botany Terminal November 2010 Electricity bill
29
3.10 Single Line Diagram with measuring devices locations
38
3.11 Energy Management System Layout
39
4.1 Different forms of quay cranes
44
4.2 Quay Cranes - Type of Lifts
45
4.3 Rail Mounted Gantries
46
4.4 Automatic Stacking Cranes
46
4.5 AC quay crane Graph of powers vs. time (second)
50
4.6 DC quay crane Graph of powers vs. time (second)
50
4.7 AC quay crane Graph of powers vs. time (second) for one loading cycle
51
4.8 DC quay crane Graph of powers vs. time (second) for one loading cycle
51
4.9 AC quay crane Graph of power factor vs. time (second) for one loading cycle
54
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4.10 DC quay crane Graph of power factor vs. time (second) for one loading cycle
54
4.11 AC quay crane Graph of THD (%) vs. time (second) for one loading cycle.
56
4.12 DC quay crane Graph of THD (%) vs. time (second) for one loading cycle.
56
4.13 Drawing showing stacking area at Melbourne Container Terminal
60
4.14 Number of container at Melbourne Container Terminal in 2007 2008
66
4.15 Percentage of 40 container, empty container and heavy container at Melbourne Container Terminal in 2007 2008
66
4.16 Average weight of container and TEU at Melbourne Container Terminal in 2007 2008
67
4.17 Calculation of average electrical demand of quay crane
69
4.18 Calculation of average electrical demand of RMG/ASC
71
5.1 Refrigeration supply system for porthole container
75
5.2 Clip on unit for transport by road
75
5.3 Portholes at the end of a porthole container
75
5.4 Integral refrigerated containers
76
5.5 Photo showing Reefer location at Melbourne Container Terminal
89
5.6 Drawing showing Reefer location at Melbourne Container Terminal
89
5.7 Electrical Demand per Reefer in 2007
96
5.8 Electrical Demand per TEU in 2007
98
5.9 Electrical Demand per Reefer in 2008
99
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5.10 Electrical Demand per TEU in 2008
100
5.11 Electrical Demand per Reefer in 2009
101
5.12 Electrical Demand per TEU in 2009
102
5.13 Mix Reefer sizes in storage at Melbourne Container Terminal
107
6.1 Reducing electrical demand by improving power factor
112
6.2 Single line diagram of substation D
117
6.3 Energy consumption without utilization of regenerative energy
120
6.4 Energy consumption without utilization of regenerative energy
121
6.5 High mast lighting at container terminal
124
6.6 Container terminal at night
124
6.7 Quay Crane load profile
128
6.8 Proposal from Powercorp using flywheel technology to limit peak demand at 500kW and allow 100kW regenerative energy to be utilized by other load
129
6.9 Proposal from S and C using super capacitor technology to limit peak demand at 400kW and capture all regenerative energy
129
7.1 East Swanson Dock terminal actual and calculated maximum electrical demands
140
7.2 West Swanson Dock terminal actual and calculated maximum electrical demands
141
7.3 Swanson Dock terminals actual and calculated maximum electrical demands
142
7.4 Port Botany terminal actual and calculated maximum electrical demands
143
7.5 Fisherman Islands terminal actual and calculated maximum electrical demands
144
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7.6 China Yantian terminal actual and calculated maximum
electrical demands
145
7.7 Canada Fairview terminal actual and calculated maximum electrical demands
146
7.8 USA Maher terminal actual and calculated maximum electrical demands
147
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List of Tables 3.1 Port Botany Terminal Meter 1 data for November 2010
30
3.2 Port Botany Terminal Meter 2 data for November 2010
31
3.3 Port Botany Terminal Summary of Electricity foe November 2010
32
4.1 Main data of Quay cranes under observation
48
4.2 Results of measurement
53
4.3 Container ship capacity and deadweight
58
4.4 Dimension and Payload of container
59
4.5 Sample of Container daily Report
61
4.6 Results of running CONTAINERS macro
63
4.7
Weight Analysis of container at Melbourne Container Terminal 65
5.1 Maximum Demand non-domestic Electrical Installation
70
5.2 Cooling capacity of Reefer Power Unit
85
5.3 Calculated Average Electrical Demand of different reefer cargo
88
5.4 Example of Reefer daily Report
91
5.5 Example of Reefer power Report
92
5.6 Results (temperature analysis) of running REEFERS macro
94
5.7 Results (weight analysis) of running REEFERS macro
95
5.8
Reefer Electrical Average demand 97
5.9 Maximum Demand calculated using different methods
104
6.1 Extract from Yantian 2005 report on QC CONSUMPTION STUDY
115
6.2 Recorded consumed real energies at substation D
119
7.1 Calculated maximum demand at Australian Container Terminal
138
7.2 Calculated maximum demand at Overseas Container Terminal
139
7.3 Comparison of calculated and actual maximum Electrical Demand 148
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List of Formulas 2.1 Basic motion formula Distance
12
2.2 Basic motion formula Distance
12
2.3 Hoist Power with Load
12
2.4 Lower Power with Load
12
2.5 Hoist acceleration Power with Load
13
2.6 Hoist deceleration Power with Load
13
2.7 Lower acceleration Power with Load
13
2.8 Lower deceleration Power with Load
13
2.9 Hoist motor acceleration Power with Load
13
2.10
Hoist motor deceleration Power with Load
13
2.11 Lower motor acceleration Power with Load
13
2.12 Lower motor deceleration Power with Load
13
2.13 Hoist total acceleration Power with Load
13
2.14 Hoist total Power with Load
13
2.15 Hoist total deceleration Power with Load
13
2.16 Lower total acceleration Power with Load
13
2.17 Lower total Power with Load
13
2.18 Lower total deceleration Power with Load
13
2.19 Hoist Power without Load
14
2.20 Lower Power without Load
14
2.21 Hoist acceleration Power without Load
14
2.22 Hoist deceleration Power without Load
14
2.23 Lower acceleration Power without Load
14
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2.24 Lower deceleration Power without Load
14
2.25 Hoist motor acceleration Power without Load
14
2.26 Hoist motor deceleration Power without Load
14
2.27 Lower motor acceleration Power without Load
14
2.28 Lower motor deceleration Power without Load
14
2.29 Hoist total acceleration Power without Load
14
2.30 Hoist total Power without Load
14
2.31 Hoist total deceleration Power without Load
14
2.32 Lower total acceleration Power without Load
14
2.33
Lower total Power without Load
14
2.34 Lower total deceleration Power without Load
15
2.35 Friction Load with Load
15
2.36 Wind Load with Load
15
2.37 Main Hoist rope inflexibility with Load
15
2.38 Static Power in Adverse Wind with Load
15
2.39 Static Power in favourable wind with Load
16
2.40 Trolley acceleration Power
16
2.41 Trolley deceleration Power with Load
16
2.42 Trolley motor acceleration Power with Load
16
2.43 Trolley motor deceleration Power with Load
16
2.44 Cross travel total acceleration Power in adverse wind with Load
16
2.45 Cross travel total Power in adverse wind with Load
16
2.46 Cross travel total deceleration Power in adverse wind with Load
16
2.46 Cross travel total acceleration Power in favourable wind with Load
16
2.48 Cross travel total Power in favourable wind with Load
16
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2.49 Cross travel total deceleration Power in favourable wind with Load
16
2.50 Friction Load without Load
16
2.51 Wind Load without Load
17
2.52 Main Hoist rope inflexibility without Load
17
2.53 Static Power in Adverse Wind without Load
17
2.54 Static Power in favourable wind without Load
17
2.55 Trolley acceleration Power without Load
17
2.56 Trolley deceleration Power without Load
17
2.57 Trolley motor acceleration Power without Load
17
2.58 Trolley motor deceleration Power without Load
17
2.59 Cross travel total acceleration Power in adverse wind without Load
17
2.60 Cross travel total Power in adverse wind without Load
17
2.61 Cross travel total deceleration Power in adverse wind without Load
17
2.62 Cross travel total acceleration Power in favourable wind without Load
17
2.63 Cross travel total Power in favourable wind without Load
17
2.64 Cross travel total deceleration Power in favourable wind without Load
18
3.1 Total consumed Energy
31
3.2
Real Demand 31
3.3 Reactive Demand
31
3.4 Apparent Demand
32
3.5 Maximum Electrical Demand
32
5.1 Increase Temperature due to Heat transfer
86
5.2 Refrigerating Capacity for Cooling
86
5.3 Average Electrical Demand
87
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7.1 Maximum Electrical Demand
133
7.2 AS/NZS:3000 calculation method Reefer Load Demand
133
7.3 AS/NZS:3000 calculation method Crane Load Demand
133
7.4 Diversity Factor Method 20 Reefer Load Demand
134
7.5 Diversity Factor Method 40 Reefer Load Demand
134
7.6 Diversity Factor Method Reefer Load Demand
135
7.7 Diversity Factor Method Crane Load Demand
135
7.8 Results from this study Reefer load Demand
136
7.9 Results from this study Crane load Demand
136
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CHAPTER ONE
Introduction
1.1 Background information
Containerization is the use of transport containers to unitize cargo for supply,
transportation and storage without the need for intermediate handling of the content.
Since the introduction in 1956 [84], containerization of cargoes is becoming ever
more widespread worldwide and almost all products are now transported by
container.
In the Container Traffic Forecast [65] published by United Nation Economic and
Social Commission for Asia and the Pacific (ESCAP), container traffic has grown
substantially from 28.7 million twenty-foot equivalent units (TEUs) in 1990 to
113.6 million TEUs in 2005. This is corresponding to an average annual compound
growth of 9 percent. The forecast suggest continued trend of increasing of the
container traffic of annual compound of 7.6 percent till 2015 taking into account the
World Economic Crisis 2008/2009. It is expected a traffic of 235.7 million TEUs in
2015.
The growth in the container traffic leads to the growth in the capacity of the
container ship as the shipping lines prefer to use larger container ship to lower the
costs. It is claimed that the transportation cost per container for the sixth generation
container ship (Post-Suezmax) may be about 30% lower than that of a typical
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5,000-6,000 TEUs container ship. Historical development of container ships [20,
22] is shown below:
1. First generation Small Feeder < 1,000 TEUs
2. Second generation Feeder 1,000 - 2,500 TEUs
3. Third generation Panamax 2,500 - 4,500/5,000 TEUs (draught of 12m)
4. Fourth generation Post-Panamax 4,500/5,000 - 10,000 TEUs (draught
of 13m)
5. Fifth generation Suezmax 10,000 - 12,000 TEUs (draught of 16.4m)
6. Sixth generation Post-Suezmax > 12,000 TEUs (draught of 21m)
With the intended increase of the cross section breadth and depth of the Suez Canal
over the coming ten years, the 18,000 TEUs container ship will also be able to pass
the Suez Canal [50]. On the other hand, a future container ship with a draught of 21
m would require existing ports to be dredged. Today, only the ports of Singapore
and Rotterdam are deep enough.
Given the expected growth of container traffic, most container terminals around the
world have terminal expansion and development projects that are either planned or
currently underway. Deploying more container handling machines, leasing more
land, changing operation mode are examples of such plans. Before spending any
money, all container terminal operators like to optimize their operation and fully
utilize their access (land, machines, labours etc.) to produce the maximum
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productivity [33, 41, 68, 71, 86]. Modelling and simulation appear to be the best
tool for this optimization task.
A lot of simulations have been done to study and optimize the operation of existing
container terminal [23, 25, 27, 32, 35, 73, 74, 81, 83, 90, 108, 130, 174, 201] or
even design a new one. These simulations are carried out to find the impacts of
terminal layout [151], allocating berthing for ship [129, 131, 132, 152, 153, 154],
predicting number of cranes for certain handling rate [127], rail logistic, truck
logistic and even impact on in land transportation. However, none have been done
for the electricity power demand and consumption or the utilization of electrical
infrastructure of a container terminal.
Planing for a new container terminal or expanding an existing container terminal
must include the power demand at the initial design stage of such development.
Increasing number and size of container handling machines: Quay Cranes (QCs),
Rail Mounted Gantries (RMGs), Automatic Stacking Cranes (ASCs) and
Refrigerated Containers (Reefers) have brought a significant increase in electrical
power demand for container terminals [112]. Accurate assessment of the projected
electrical load is of critical importance as this electrical demand is used for:
- sizing and selection of principal electrical assets, thus impacting on the
capital cost of the electrical infrastructure,
- request an update or new electrical supply from the electrical power supply
company. Capital cost of electrical supply could be very high if the current
electrical network can not provide the requested demand.
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1.2. Research aims and objectives
As container terminal is a specific engineering field and currently there is no
standard or guidance for electrical engineers to accurately calculate the electrical
demand [6], all are depended on the experiences of those engineers for this
estimation. This would normally lead to an over design of electrical infrastructure
and resulting in a very costly exercise if a new electrical switching station would be
built to supply the projected load demand. For example, in a recent re-development
of a container terminal in Australia, a load demand of 16MVA was stated for this
container terminal with 8 QCs, 5 RMGs and 800 refrigerated containers. A new
electrical switching station was required to supply such demand with a total cost of
around AUD 10 million. A similar size container terminal in Australia has an actual
load demand of only 4MVA.
There are number of private studies of energy consumption and power supply at
several container terminals that concern about their electrical bills [95].
Presentations [18] and information [70, 98, 136] about electrical demand and
energy usage of electrical machines are now a requirement as part of technical
documents to be submitted to electrical supply tenders called by all container
terminal operators.
The main aims of this research are: how to estimate/calculate the maximum
electrical demand of a container terminal with known number of electrical
equipments? What is the likely electrical energy usage for a container terminal with
a known through put? A practical approach is used to find out the answers:
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x With the permission of the container terminal management, installing a
power monitoring system consist of a server and number of digital power
meters for logging electrical data. At the same time, details of containers at
the terminal are provided for every day and monthly electrical invoices are
also obtained for comparison. . The monthly electrical invoices are also
obtained for confirmation of the analysed results. Data have been collected
for over two (2) years.
x Learning the spreadsheet simulation technique from simulation conferences
papers [165, 166, 168, 169, 171, 177, 178, 179, 181, 182, 183, 184].
x Calculation and spread sheet simulation are performed to estimate the
electrical load of the machine. Examining the working of the smart meter,
how power supply company calculate the demand and analysing the
collected data. Results are used for estimating the total demand of the
terminal.
x Electrical energy consumptions at several other container terminals around
the world are also obtained to confirm the study results.
The environment concern of green house emission is also looked at by investigating
how to reduce such electrical demand end energy consumption - the design of
electrical network, the application of the new technical innovations such as
synchronizing operation of multiple machines and using peak lopping device.
This research looks into the gap left by previous researches and studies related to
container terminals. Hopefully, it will clarify some electrical issues contribute to
the knowledge of designing and operation of the container terminals.
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1.3. Outline of the thesis
This thesis consists of eight chapters. In the next chapter, an introduction to
electrical power demand and energy usage at a container terminal and review of
related literature are presented. Chapter 3 outlines the operating environment of
container terminal, identifies the electrical assets to be studied, investigate how
electrical consumption is measured and charged then describe the set up of data
collection scheme. Chapter 4 looks at the container handling machines group
consists of Quay Cranes (QCs), Rail Mounted Gantries (RMGs) and Automatic
Stacking Cranes (ASCs). A brief discussion and focus on what would be studied
followed by obtaining the quay cranes specifications and profiles, discusses the
drive systems (DC and AC) and analysing the weights of containers in stack of
Melbourne Container Terminal from collected data and finally calculate the
electrical demand and energy usage of the container handling machines group.
Chapter 5 investigates the refrigerated containers, methods of calculating the
refrigerated containers electrical demand, describes another way of calculation.
The actual (more than two years) measurements and calculation results are
tabulated for comparison. Chapter 6 discusses several ways of reducing the
maximum electrical demand and energy usage at container terminal ranging from
the design of electrical network to utilise the regenerative energy, requesting for net
metering scheme, the use of energy storage and peak lopping devices and lighting
level at the container terminal. Chapter 7 verifies the finding of this study by
showing the comparison between the actual electrical demand and the calculated
maximum electrical demand of several container terminals around the world.
Finally, chapter 8 will summarised the thesis, make concluding remarks as well as
recommendations for future research.
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CHAPTER TWO
Literature Review
To the best of the authors knowledge from the literature review and long time
working in the port, there was no published academic research into the electrical
energy usage and demand at container terminal. Literatures [49, 51, 52, 118, 195,
196, 197, 200, 205] on the rail/traction area had also been reviewed to find any
applicable information for use. Because of the lack of published research in this
field, the author had to rely on the commercial articles written for magazines
specialised in this field, the presentation at commercial conference as well as the
internal reports of various container terminal operators and electrical supply
companies for review and gather information.
The reviewed papers are grouped into following categories:
x container terminal overview papers to provide an understanding of the
operation of container terminal,
x electrical energy usage and demand papers to find what have been done in
this field and
x formulas for electrical power demand calculation.
2.1 Overview Papers
A detailed literature review on the transhipment of containers at a container
terminal was given by Vis and Koster in 2002 [135]. Different type of material
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handling as well as planning and control level involving the movement of
containers. The processes at container terminal are discussed next with the detailed
descriptions of each process with reference to relevant information when required.
These pre berth allocation, unload and loading of container ships, transportation of
containers from ship to storage area, stacking these containers and delivering them
to owner directly or by inter-terminal transportation. In the conclusion, they stated
that the majority of published papers only address single type of handling machine
so that the future work shall be concentrate in addressing multiple types of handling
machines for optimising the operation at container terminal.
On the same topic, Stahlbock and Vob [54] provided a comprehensive literature
review of research on optimising methods applied to container terminal operations.
The paper began with an update on the new challenges that the container terminal
operators have to overcome, especially with the requirement of handling new mega
size container ships capable of carrying 10,000 TEU to 12,000 TEU. They then
discussed the container terminal operation system and its sub system such as the
handling equipment, human recourses and supporting system. Research on
optimising methods was discussed in details of few particular subsystems that have
big impact on the operation such as berth allocation and stacking logistics. They
concluded the review with a summary; they also identified and suggested a number
of promising and interesting topics for future research.
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2.2 Electrical Energy Usage and Demand Papers
It was reported early this year (March 2012) in the Port Technology International
[7] that a simulation model had been developed by Kim Le of AECOM for studying
the electric power of yard cranes. The concern about the increasing of required
electrical demand, especially when a large number of cranes are installed and
connected to the electrical grid at the container terminal, and the lack of suitable
method for calculating this demand was the reason for such study. The most
interesting result from this simulation study is that for 36 yard cranes with 700 KW
demand each totalling of 25,200 kW, the average demand of all 36 machines is only
1,000 kW and for a percentile of 99%, a demand of 3,240 kW is required. However,
the critical information is not provided: yard crane electrical data, container weight,
travel distances etc. for the readers to make use of the results. To an electrical
engineer reader, it appeared to have mixed up between electrical energy
consumption (kWHr) and electrical demand (kW) terminologies.
In the Efficient use of energy in container cranes article of the same magazine
Port Technology International, edition 48 [26], Fredrik Johanson of ABB described
the regenerative energy issue of electrical powered cranes and suggested ways for
utilising this energy especially for automatic stacking cranes.
In the Driving innovation: high handling efficiency, low energy use article of the
Port Technology International, edition 47 [28], Gottwald Port Technology described
a successful innovation for its mobile crane using energy storage system to
capture the regenerative energy when the crane lowering and discharge this energy
when the crane hoisting.
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Another useful information was described in the Crane life cycle costs in the Port
Technology International edition 20 [128] by Gerhard Fischer of Siemens that the
average net amount of energy required to move a container was 1.94 kWHr.
At the Terminal Operators Conference in 2005, Robert Reid of Robert Reid and
Associates had present a paper titled Design, Installation and Electrical
Management of Container Terminals with Large Electrical Demand [110]. An
overview of the electrical infrastructure of the container terminal and regulatory
requirements in Australia had been discussed. The finance impact as well as
benefits would be achieved by reducing the electrical demand. In discussion of the
electrical demand, the paper raised concern about the lack of accurate method for
calculating the maximum electrical demand. The actual facts were also presented:
average weight of container traffic, the large size of container handling cranes as
well as their characteristic, the affect of number of refrigerated containers in the
terminal, and the actual electrical energy consumption by the container terminal.
The paper concluded by stating that accurately calculating the maximum electrical
demand is really needed for designing a new container terminal or upgrading the
existing one.
In a presentation to DP World the terminal operator at Brisbane Port in 2011 [18]
for an Automatic Stacking Cranes (ASC) project, G Nordman of ABB presented an
Excel spreadsheet simulation for 12 ASCs. With a known operating characteristic of
one ASC, the simulation was performed with various operating conditions such as
fix hoisting delay between machines and assuming operating of multiple ASCs at
the same time would not cause any issue for the electrical supply network.
Following data is of interested:
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11
For one ASC Maximum Demand 930 kW
Average Demand 69 kW
For 12 ASCs at hoisting delay of 20 seconds:
Maximum Demand 2,167 kW
Average Demand 822 kW
2.3 Formula for Electrical Power calculation
Part of tender documents submitted for bidding to supply container handling cranes
is that theoretical calculation of electrical power under pre-set operating conditions.
The author had access to the document of successful tenders providing the container
crane to various container terminals in Australia [70, 98, 136]. For this study,
electrical demand calculation would have to be performed and reviewing these
documents for formulas used in electrical power calculation has the advantage of all
needed formulas are available saving time in reviewing a lot of different text books
[121, 207, 210] for needed formulas.
When calculating the maximum electrical demand, boom hoist and long travel
motions can be ignored because:
x the boom motion is only used to put the crane in the working position to
start loading/unloading containers and to stow the boom at the end of its
work,
x other motions are not available when boom hoist is in use.
x the booms electrical motor is not as large as the hoists electrical motor, the
demand is not the maximum demand
x other motions are not available when long travel is in use
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12
x the long travels electrical motor is not as large as the hoists electrical
motor, the demand is not the maximum demand
Basic motion formulas:
vts (Eq. 2.1)
tvats 02
21 (Eq. 2.2)
Where v speed in m/sec
v0 initial speed in m/sec
s travel distance in m
t travel time in second
The following naming index conventions are used on all formulas in this section:
Nxy Power (in Watts) with: x = 1 for motion with load, x = 2 for motion without load y = 1, 2, for different powers Pwxyz Total Power (in Watts) with: w : w = 1 for motion with load and w = 2 for motion without
load x : H for Hoisting, L for Lowering, XT for cross Travel and
LT for Long Travel. y : A for acceleration, D for deceleration & nothing for motion
at constant speed z : W for travel against wind, NW for travel with wind, nothing
for hoist motion
A. Hoist/Lower motion The following formulas are used to calculate the average demand of the hoist motion: With load (lift container)
Hoist Power u
VgLSLLN*60
**)( 111 (Eq. 2.3)
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13
Lower Power uV
gLSLLN *60
**)( 312 (Eq. 2.4)
Hoist acceleration Power ut
VLSLLN*
)60/(*)(1
21
13 (Eq. 2.5)
Hoist deceleration Power ut
VLSLLN *)60/(*)(2
21
14 (Eq. 2.6)
Lower acceleration Power ut
VLSLLN *)60/(*)(5
23
15 (Eq. 2.7)
Lower deceleration Power ut
VLSLLN*
)60/(*)(
6
23
16 (Eq. 2.8)
Hoist motor accel. Power 1
212
17 *1000)60/**2(*
tnWKN h
S (Eq. 2.9)
Hoist motor decel. Power 2
212
18 *1000)60/**2(*
tnWKN h
S (Eq. 2.10)
Lower motor accel. Power
5
21132
19 *1000)60/*)/(**2(
*t
nVVWKN hS
(Eq. 2.11)
Lower motor decal. Power
6
21132
20 *1000)60/*)/(**2(
*t
nVVWKN h
S (Eq. 2.12)
Hoist accel. Power (W) 1713111 NNNP HA (Eq. 2.13)
Hoist Power (W) 111 NP H (Eq. 2.14)
Hoist decel. Power (W) 1814111 NNNP HD (Eq. 2.15)
Lower accel. Power (W) 1915121 NNNP LA (Eq. 2.16)
Lower Power (W) 121 NP L (Eq. 2.17)
Lower decel. Power (W) 2016121 NNNP LD (Eq. 2.18)
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14
No load - without load
Hoist Power u
VgLSN*60
** 221 (Eq. 2.19)
Lower Power uVgLSN *60
** 422 (Eq. 2.20)
Hoist acceleration Power ut
VLSN*
)60/(*3
22
23 (Eq. 2.21)
Hoist deceleration Power ut
VLSN *)60/(*4
22
24 (Eq. 2.22)
Lower acceleration Power ut
VLSN *)60/(*7
24
25 (Eq. 2.23)
Lower deceleration Power ut
VLSN*
)60/(*8
24
26 (Eq. 2.24)
Hoist motor accel. Power 3
222
27 *1000)60/**2(*
tnWKN S (Eq. 2.25)
Hoist motor decel. Power 4
222
28 *1000)60/**2(*
tnWKN S (Eq. 2.26)
Lower motor accel. Power
7
2224
229 *1000
)60
*)/(**2(*
t
nVVWKN
S (Eq.2.27)
Lower motor decel. Power
8
2224
230 *1000
)60
*)/(*14.3*2(*
t
nVVWKN (Eq. 2.28)
Hoist accel. Power (W) 2723212 N N N HAP (Eq. 2.29)
Hoist Power (W) 212 N HP (Eq. 2.30)
Hoist decel. Power (W) 2824212 N N N HDP (Eq. 2.31)
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15
Lower accel. Power (W) 2925222 N N N LAP (Eq. 2.32)
Lower Power (W) 222 N LP (Eq. 2.33)
Lower decel. Power (W) 3026222 N N N LDP (Eq. 2.34) Where LL Weight of load (container) in tones LS Weight of spreader & headblock (lifting device) in tones V1 Hoist speed with load in m/min V2 Hoist speed without load in m/min V3 Lower speed with load in m/min V4 Lower speed without load in m/min t1 Hoist acceleration time with load in seconds t2 Hoist deceleration time with load in seconds t3 Hoist acceleration time without load in seconds t4 Hoist deceleration time without load in seconds t5 Lower acceleration time with load in seconds t6 Lower deceleration time with load in seconds t7 Lower acceleration time without load in seconds t8 Lower deceleration time without load in seconds n1 Hoist motor speed with load in rpm n2 Hoist motor speed without load in rpm WKh2 Total rotational inertia (include gearbox, drum, load) in kgm2 u Overall efficiency g Gravity (9.81m/sec2) Constant Pi = 3.14 N1i Hoist/Lower with load Power in Watts (i = 1,2,3.9) N2i Hoist/Lower without load Power in Watts (i = 1,2,3.9) B. Cross Travel motion The following formulas are used to calculate the average demand of the hoist motion: With load (container) Friction Load cLSLLTLL *)(11 (Eq. 2.35) Wind Load QAL *112 (Eq. 2.36)
Main hoist rope inflexibility load 2
)(*)1(*1000 313
LSLLvL (Eq. 2.37)
Static power in adverse wind
u
VgLLLN xt
*1000*60**)( 13121111 (Eq. 2.38)
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16
Static power in favourable wind
u
VgLLN xt
*1000*60**)( 131112 (Eq. 2.39)
Trolley acceleration power ut
V
LSLLTLNxt
xt
*
)60
(*)(
1
2
13 (Eq. 2.40)
Trolley deceleration power 1
214 *)60
(*xt
xt
tuVTLN (Eq. 2.41)
Motor acceleration power 1
2
215 *1000
)60
**2(*
xt
xt
xtt
n
WKNS
(Eq. 2.42)
Motor deceleration power 1
2
216 *1000
)60
**2(*
xt
xt
xtt
n
WKNS
(Eq. 2.43)
Cross travel acc. power in adverse wind (W) 1513111 NNNP LXTAW (Eq. 2.44) Cross travel power in adverse wind (W) 111 NP XTLW (Eq. 2.45) Cross travel deceleration power in adverse wind (W)
1614111 NNNP XTDW (Eq. 2.46) Cross travel acc. power in favourable wind (W) 1513121 NNNP XTANW (Eq. 2.47) Cross travel power in favourable wind (W) 121 NP XTNW (Eq. 2.48) Cross travel decal. power in favourable wind (W)
1614121 NNNP XTDNW (Eq. 2.49) Cross travel without load
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17
Friction Load cLSTLL *)(21 (Eq. 2.50) Wind Load QAL *222 (Eq. 2.51)
Main hoist rope inflexibility load 2
*)1(*1000 323
LSvL (Eq. 2.52)
Static power in adverse wind (W)
u
VgLLLN xt*1000*60
**)5.0( 23222121 (Eq. 2.53)
Static power in favourable wind (W)
uVgLLN xt
*1000*60**)( 232122 (Eq. 2.54)
Trolley acceleration power (W) ut
V
LSTLNxt
xt
*
)60
(*)(
2
2
23 (Eq. 2.55)
Trolley deceleration power (W) 2
224 *)60
(*)(xt
xt
tuVLSTLN (Eq. 2.56)
Motor acceleration power (W) 12
2
225 *1000
)60
**2(*
xt
xt
xtt
n
WKNS
(Eq. 2.57)
Motor deceleration power (W) 2
2
226 *1000
)60
**2(*
xt
xt
xtt
n
WKNS
(Eq. 2.58)
Cross travel acc. power in adverse wind (W) 2523212 NNNP XTAW (Eq. 2.59) Cross travel power in adverse wind (W) 212 NP XTW (Eq. 2.60) Cross travel deceleration power in adverse wind (W)
2624212 NNNP XTDW (Eq. 2.61) Cross travel acc. power in favourable wind (W)
2523222 NNNP XTANW (Eq. 2.62)
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18
Cross travel power in favourable wind (W) 222 NP XTNW (Eq. 2.63) Cross travel decal. power in favourable wind (W) 2624222 NNNP XTDNW (Eq. 2.64) Where LL Weight of load (container) in tones LS Weight of spreader & headblock (lifting device) in tones TL Weight of trolley in tones A1 Wind area with load in m2 A2 Wind area without load in m2 Q Wind pressure in kg/m2 v Sheave efficiency Vxt Trolley speed in m/min txt1 Cross travel acceleration time in seconds txt2 Cross travel deceleration time in seconds nxt Cross travel motor speed in rpm WKxt2 Total rotational inertia (include gearbox, drum, load) in kgm2 u Overall efficiency g Gravity (9.81m/sec2) c Friction coefficient in kg/t Constant Pi = 3.14 N1i Cross Travel with load Power in Watts (i = 1,2,3.9) N2i Cross Travel without load Power in Watts (i = 1,2,3.9)
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19
CHAPTER THREE
Electrical Assets Identification and Set up Data
Collection Scheme
Before any study of electrical usage and demand at the container terminal can be
started, all electric powered assets have to be identified. The term electric powered
asset or electrical asset refers to the asset that actual connects to electrical grid and
consumes electricity not asset that providing electric power. For example, quay
cranes are electrical assets but the high voltage switchgears connecting these cranes
to the electrical grid are not.
Understanding of how energy and demand are defined, measured and charged by
the power supply companies (the Utilities) is also important as it help to focus the
study as well as deciding what and how to collect data for this study.
Three main topics will be described and discussed in this chapter:
- Identification of all electric powered assets at container terminal,
- Electricity bills and measured data supplied by the Utilities to focus the
study and set up data collection scheme,
- Describe the data collection system at Melbourne Container Terminal.
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20
3.1 Identification of electrical assets at container terminal
3.1.1 Processes at container terminal
The container terminal knows in advance the expected arrival time of a container
ship, the number of containers to be exchanged and the ship stowage plan so that a
unloading plan and/or loading plan can be prepared, equipment and labour can be
allocated to work on that container ship. Figure 3.1 shows a typical container ship
stowage plan that is the lay out of the ship and container positions.
When the container ship arrives, QCs as shown in Figure 3.2 working according to
a prepared unloading plan take the import containers off the ship and put on the
wharf. The containers are then transferred to the storage stack be transport vehicles
such as Forklifts or Straddle Carriers (SCs) Figure 3.3 - that travel between the
QCs and the storage stack.
Figure 3.1 Stowage plan of a container Ship
-
21
Figure 3.2 Quay Cranes Figure 3.3 Straddle Carrier
Figure 3.4 Container ship unloading plan
-
22
Equipment, such as straddle carriers (SCs), Rubber Tyred Gantries (RTGs), Rail
Mounted Gantries (RMGs) then put these containers into the storage stack
according to a prepared storage plan. Figure 3.4 shows a typical unloading plan
with container identification and details, position on the ship and unloading
sequence.
The storage stack consists of a number of lanes where containers can be stored for a
certain period. Dry cargo containers and refrigerated containers are stored in
different areas. Containers can be stored several high depend on the equipment used
in this storage stack. Melbourne Container Terminal use mainly SCs for container
transportation and stacking. Its storage stack is shown in Figure 3.5.
After a certain period the containers are retrieved from the stack and transported by
vehicles to transportation modes like trucks or trains to leave the container terminal.
Figure 3.6 shows SC delivers container to the truck.
Figure 3.5 Melbourne Container Terminal storage stack
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23
Figure 3.6 Straddle Carrier deliver container to truck
To load export containers onto a ship, these processes are also executed in reverse
order. A typical loading plan is shown in Figure 3.7 and Figure 3.8 provides a
summary of container processes at a Container Terminal.
Most of the container terminals make use of manned equipments. However, a few
terminals are semi-automated using unmanned equipment for transport of
containers such as driver less SCs are used in Patrick Terminal in Brisbane, driver
less Rail Mounted Gantries (RTGs) are also tried at Patrick Terminal in Sydney,
some terminals in Rotterdam use Automated Guided Vehicles (AGVs) and
Automated Stacking Cranes (ASCs). Australian Container Terminals in Brisbane
and Sydney are currently re-developing their sites for use ASCs.
-
24
Figure 3.7 Container ship loading plan
-
25
Figure 3.8 Processes at Container Terminal
-
26
3.1.2 Electrical assets at container terminal
As a large electrical user and having a number of machines powered at high voltage
(HV) typically at 11kV level, container terminals are usually under HV tariff.
Following the above description, container terminal administration office is the first
area to look at for electrical assets. Typically, it consists of the following:
x working areas and amenities (general office, first aid office, meeting room,
canteen, toilet, ) for its work forces,
x control tower/room for computer system to observe and monitor all terminal
activities,
x air conditioning, lighting and communication systems.
Electrical power at low voltage (three phase 415V in Australia) is required for these
services. Supply is normally via a step down transformer located near the office to
reduce the voltage drop.
Next type of electrical asset is the container handling equipment group: QCs, RTGs,
RMGs, ASCs, AGVs, SCs and Forklift. However, RTGs, AGVs, SCs and Forklift
are mobile machines which are either not electric powered or not connected to
electric grid. In other words, they are not electrical assets for the purposes of this
study. QCs, RMGs and ASCs are giant and very fast electric powered machines
which give the impression that they use a high amount of energy and require a very
high electrical demand. Due to their size and the capability of travel a relative long
distance (few hundreds meters), they are powered by HV, typically at 11kV.
-
27
Next electrical asset would be the refrigerated containers that require low voltage
electrical power to keep their cargo at the correct temperatures. Designated areas
with electrical infrastructure to allow these refrigerated containers to be connected
to the electrical grid are in the storage stack. These designated areas are normally
located close to the electrical substation to limit the voltage drop.
As container terminals are operated on 24 hours a day and 7 days a week basic,
lightings are required for night operation. Low voltage electrical supply to these
lightings is from the mention electrical substations.
A maintenance workshop is also a requirement at any container terminal; it is where
the repair and maintenance works to be carried out to keep all electrical assets in
good working order. Welding machines, lathes, power tools, measurement
instruments, spares,.. are in this workshop which required low voltage electric
power supply.
These electrical assets are divided into three groups for detailed study:
x Container cranes group consists of QCs, RMGs and ASCs assets
x Refrigerated containers group
x Other load group consists of Office, Workshop and Lighting assets
Container group will be studied in Chapter 4, Chapter 5 investigates the refrigerated
container group. Demand of the other load group is well regulated and could be
calculated using the AS/NZS 3000 [62] or Construction handbook [21, 34] , it is the
responsibility of the building designer to provide the estimated demand; the
installed demand of this load group was taken as the maximum demand for this
study.
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28
3.2 Definition of Electrical Demand
Electrical demand could mean different thing among the Utilities. As the purpose of
this study is to calculate the electrical maximum demand at the container terminal, it
is important that a clear definition of the term demand is needed ([99] provides
basic information). This was achieved by checking information provided by the
Utilities, analysing the actual electricity bill and examining measuring devices.
3.2.1 Definition from the Utilities
The following definitions are obtained from several different Utilities in Australia:
United Energy
Maximum Demand = Energy consumption over hr period/ Time (1/2 hr). The Rolling Peak Demand Charge is based on the highest power (kVA at the highest kW) delivered during Peak periods (defined as 7am to 7pm Local Time weekdays excluding public holidays) over 12 months to the end of the billing period.
Powercor
Actual demand, which is measured as the energy consumption recorded over the demand integration period divided by the demand integration period in hours (the demand integration period is 15 minutes.
Energex
The customers connection point has a meter installed that is capable of measuring energy consumption (kW.h) and demand (kW). This meter records total energy consumption (kW.h) and demand over 30 minute periods. A customers demand is the average demand (kW) over the 30 minute period.
Western Power
The metered demand (MD) is a rolling 12-month maximum haft-hourly demand.
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29
The electrical demand is actually calculated as defined above was confirmed in the
next section by examining the electrical bills of the container terminal and the raw
measured electrical usage.
3.2.2 Definition from Electricity Bills and measured energy
Electricity bill of an industrial HV customer is different from a residential LV
customer. By law, all the different charges have to be disclosed. Figure 3.9 shows
the electricity bill of the container terminal in Port Botany Sydney for November
2010. For the purposes of this study, the following information is of interested:
Total energy usage: 826,565 kWh and Maximum demand: 2317.41 kVA
Figure 3.9 Port Botany terminal November 2010 Electricity bill
-
30
It was noted that there is no information on the feed back energy from the container
terminal (when container handling machine in lowering mode), by experience it is
small amount and ignored by the Utilities. The Utilities provided the electrical data
as requested by the container terminal operator to ensure the charges were correct.
As shown on the electricity bill, there are two meters so that two set of metered data
were provided. Data are time stamped for every 30 minutes during November 2010.
Table 3.1 and Table 3.2 list only part of the electrical data as full listing is not
necessary.
Table 3.1 Port Botany terminal Meter 1 data for November 2010
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31
Table 3.2 Port Botany terminal Meter 2 data for November 2010
Calculation was performed to find the total energy usage and maximum demand
during November 2010. Calculations are:
kWhyUsageTotalEnerg (Eq. 3.1)
kWhh
kWhkW *2 as h = 30 minutes = 0.5 hours (Eq. 3.2)
kVArhh
kVArhkVAr *2 as h = 30 minutes = 0.5 hours (Eq. 3.3)
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32
22 kVArkWkVA (Eq. 3.4)
)(kVAMAXDemandMax (Eq. 3.5)
Calculations are also shown in Table 3.1 and Table 3.2 and the results are
summarised in Table 3.3
Table 3.3 Port Botany terminal Summary of Electricity November 2010
Electricity Bill Metered Data Unit Energy Usage Meter 1 559,913 559,840 kWh Meter 2 266,652 266,636 kWh Total 826,565 826,476 kWh Max Demand 2317.41 2301.40 kVA
The same results were found for all the electricity bills and metered data in 2010. It
was concluded that as defined by the Utilities, electrical demand is indeed
calculated from the metered energies over a time period of 30 minutes.
Digital meters are now used by the Utilities to measure the electrical usage; they are
capable of measuring the electrical demand. Information of how the digital meters
measure the electrical demand was examining in the next section for the definition.
3.2.3 Definition from the Digital Power meters
All digital power meters installed at large users including container terminal are
capable of recording energy both ways: deliver (from the electrical grid to the
customer (positive)) and receive (from the customer to the electrical grid
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33
(negative)). However, unless the received energy is from small source (solar) or
agreed generator set the Utilities would not recognize this feed back energy.
The maximum electrical demand is calculated from the measured energies over a
period of 30 minutes as shown in the previous section. It is known that digital
meters are capable measure and calculate a lot more electrical parameters especially
the electrical demand value. It is possible that some Utilities may use this value
instead of calculate as previous section. To ensure this possibility would not affect
the out come, definition of electrical demand measured by the digital meters was
examined in this section.
Following descriptions are extracted from the manuals of some of the digital
meters that used at container terminals around the world:
ION 7300 series Power & Energy Meter from Schneider Electric [69]
Demand is a measure of average power consumption over a fixed time
interval. Peak (or maximum) demand is the highest demand level recorded
over the billing period.
Quantum Q1000 Multifunction Meter from SchlumbergerSema [156]
Demand is the average value of a measured quantity over a specified time.
9300 Series Power Meter from Siemens [11]
The demand modules (both Thermal Demand modules and Sliding Window
Demand module) are configured to calculate the average current demand
and kW, kVAR and kVA demand.
-
34
Mk Genius and Mk6E Energy Meters from EDMI [114]
The demand for the period is simply the accumulated energy divided by the
fraction of an hour that the demand period is.
DIN Integra 500 Series from Crompton [3]
Most electricity utilities base their charges on power consumption,
historically using a thermal maximum demand indicator (MDI) to measure
peak power consumption averaged over a number of minutes, thus avoiding
artificially high readings caused by surges.
It was confirmed that the digital meters calculate the electrical demand in the same
manner as the Utilities do from their metered energy values. That means value of
electrical demand is the same either it was read from the digital meter or calculated
by the Utilities.
The important result from the study so far is that electrical demand is the average
demand over a measure period. The measure period is 30 minutes for Melbourne
Container Terminal and Sydney Port Botany Container Terminal.
3.3 Focusing study on average electrical demand
With the understanding of maximum electrical demand as discussed in previous
section, the maximum demand calculation in later section would be the calculation
of the maximum average demand instead of the peak demand. Reasons for this
decision were given below.
-
35
3.3.1 Reasons for focusing study on average demand instead of peak demand
Recall from previous section, the electrical demand is the average demand over a
measure period that is normally 15 minutes or 30 minutes. Since the main purpose
of this study was to calculate the maximum electrical demand at container terminal
for negotiation the power supply contract either new supply or an upgrade one,
similar term (the average demand) should be used.
Some digital power meters do have the ability to calculate and record the
instantaneous maximum demand (secondly). However, as there is no way of
distinguishing between the actual electrical demand from the user and the network
disturbances; this ability of the meter was usually ignored.
An analogue maximum demand ammeter, such as BIQ96 from Ziegler, could also
be used to measure the maximum current demand then maximum power demand
could be calculated if required. Information from http://www.ziegler-
instruments.com/pdf/Bieq-c-ch.pdf (accessed on 22 May 2012) states that: The
thermal bimetallic movement indicates the mean rms value over 15 minutes
(optional 8 min.) And deflects a reset-table red slave pointer which shows the
maximum value reached. It was noted that peak demand was not measured.
Although peak electrical demand is important for any electrical network, it may
cause voltage flickering and trigger the supply interruption on a weak network, peak
demand is really the protection issue, which is out of this study scope. It is possible
to reduce this peak demand value to a manageable figure by using a synchronized
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36
movements (central control) [42] scheme or using a peak lopping device that
would be discussed in Chapter 6.
3.3.2 Decision of focusing the study on average demand
A container terminal with a large number of container handling cranes would face a
very large value of maximum electrical demand if peak values were used.
Information of how electrical energy and demand were measure, calculated and
charged at container terminal together with the above reasons, using average
electrical demand was the correct way to calculate/estimate the maximum electrical
demand of a container terminal.
3.4 Set up at Melbourne Container Terminal for collecting data
With the approval and permission of Patrick management team, the new 11kV HV
reticulation with an Energy Management System (EMS) was designed and installed
at Swanson Dock in the Port of Melbourne. The change over from the old electrical
supply network to the new ones without interruption to the daily operation of the
terminal was completed in early 2006.
The selected EMS was the Power Logic System Management Software from
Schneider Electric (previously owned by Square D) because it was the only system
that provides a complete solution at that time. The EMS was designed for the ease
of communicating and collecting measured electrical data from a large range of
power meters, protection relays as well as tripping units of low voltage circuit
breakers especially for devices from Schneider Electric.
-
37
Figure 3.10 shows the HV single line diagram and location of measuring devices
while Figure 3.11 shows the layout of the EMS system.
For a fast changing electrical load, such that the QC, RMG and ASC, Schneiders
circuit monitor CM3250 was used. This device is a powerful power meter with in
built memory large enough to record electrical data every second for at least 5
hours.
For a slow changing or steady load, such as the refrigerated containers, metering
features of the digital protection relay (SEPAM series 40) and digital tripping
circuit of circuit breaker (MicroLogic 5) were utilised. These devices do not have
built-in memory, the required electrical values were measured and calculated then
pass on to the EMS server when there was a data collect signal was issued from
the EMS server. Electrical data collection period can be varied between 1 minute
and 1 hour.
Power Logic System Management Software version 4 was installed on a computer
server which runs Windows Server 2003 operating software. Electrical data,
voltages, currents, powers, energies, power factor and harmonics from each of the
devices (shown in Figure 3.11) were collected and save in a database every 15
minutes. Historical data could be archived when required.
The system was set up as a stand alone system that was not connected to the
container terminal computer network for security reasons. Remotely access was via
the World Wide Web by using the service of Iburst wireless network.
Unfortunately, the Iburst network was closed several years ago and the only way to
access this system was via local direct log in to the server.
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38
Figu
re3.
10
S
ingl
e L
ine
Dia
gram
with
mea
suri
ng d
evic
es lo
catio
ns
-
39
Figu
re 3
.11
Ene
rgy
Man
agem
ent S
yste
m la
yout
-
40
With permission from management team of Patrick, the Melbourne Container
Terminal Operator, and utilizing the fast 1 second data recording feature of the
CM3250, load profiles of number of QCs were obtained. The QCs electrical
specifications, characteristic, measure conditions and results would be discussed in
Chapter 4.
The management team also permitted the daily weekday reports of number of
refrigerated containers and dry cargo containers that were in storage stack of the
terminal be generated and provided via email. These reports would be discussed in
Chapter 4 and Chapter 5.
Although all circuit monitor CM3250s and Power Logic System Management
Software V4 are still in working order providing invaluable data for the study and
any future work, they are discontinued and no longer available, Schneider Electric
claims latest software version, Power Logic ION Enterprise, and newer
measurement devices would be more user friendly and provide better results.
3.5 Conclusions
Understanding the processes at container terminals helps to identify the electrical
assets and focus the study on interested areas.
The definition of the electrical demand term that is referred to by the Utilities is
clarified by reviewing the Utilities electricity bills, examining the raw data of
measured electrical parameters and investigating how those electrical parameters
are defined in modern digital power meters (smart meters), it is confirmed that
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electrical demand is the average demand over a measure period (usually 15
minutes or 30 minutes period) and is not the instantaneous demand. The tasks
of finding the maximum demand of electrical assets became easier with this
confirmation.
With the measurement scheme set up for data collection as described, the studyied
results could be verified. The electrical energy usage and maximum demand of
container cranes group would be investigated in the next chapter Chapter 4
Container Handling Crane.
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CHAPTER FOUR
Container Handling Crane
With the electrical assets of container terminal have been identified in previous
chapter, the electrical demand and energy usage for the big machine group
container handling cranes could now be studied. These machines are used to:
x move containers from container ship to ground or via versa (QCs),
x move containers into stacking area, shuffle them within the stacking area or
move containers out of stacking area for delivery either with driver (RMGs)
or driverless (ASC).
This chapter began with a brief discussion on these machines and their operation
then investigates the following:
x Quay crane profile record load profiles of similar quay cranes with AC
drive and DC drive and compare the results for contribution to the AC verus
DC drive debate,
x Container weight payload of container, capacity and deadweight of
container ship and analysing actual weights of containers (daily data
collected more than one year) in stack of Melbourne Container Terminal for
contribution to the debate of what size (lifting capacity) of quay crane is
needed.
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The reasons why this study was only focusing on the maximum average demand
instead of the peak instantaneous demand would be discussed before demand
calculations were performed and conclusions were drawn.
4.1 Brief Discussion of container handling cranes
A modern container terminal would be dominated by the giant quay cranes that can
reach out over the ships to load or unload containers. They are mounted on rails and
will be able to long travel up and down the quay to exactly align themselves with
the bays in or over the ships hold, where the container is to be handled. The
outreach of the horizontal boom permits a trolley to cross travel from over the quay
to over the ship, a spreader with four locks suspended from the trolley. These locks
nest into the four corners of the containers, make fast and enable the container to be
hoisted out of (or lowered into) the ship hold. A crane driver in his cab alongside
the trolley has an excellent view of the process he is controlling.
Apart from the sizes of the quay cranes that are capable of serving different type of
container ships (Panamax, Post Panamax,), quay cranes are different in look: A
frame quay cranes are the most common cranes as they are the lightest and
cheapest quay cranes that can be built. Articulated boom or goose neck quay cranes
are used when there is a restriction in cranes height. Under severe crane height
restriction due to the container terminal is on the adjacent airports flight path,
shuttle boom or low profile quay cranes have to be used. Figure 4.1 shows these
types of quay cranes.
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Another way of classifying quay cranes is their lifting capability or safe working
load (SWL) and how they lift containers. As 30 tones is the SWL of each 20 or
40 container, latest design tandem lift quay crane capable of lifting 6 x 20
containers should have the rated load of 180 tones. Figure 4.2 shows different types
of lifts.
Figure 4.1 Different forms of quay cranes
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Source : www.lifttech.net
Figure 4.2 Quay cranes - Types of Lifts
On the quay ground handling equipment (straddle carriers, fork lifts or automatic
guided vehicles) moves the containers from the quay cranes to the stack and via
versa. The container is then moved into stacking area by the rail mounted gantries
(RMGs) or driverless automatic stacking cranes (ASCs). The same machine will
deliver containers to the truck or rail when required. In general, these machines are
very similar to the quay cranes without the boom motion, hoist/lower and cross
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travel motions are for a short distance only. RMGs are shown in Figure 4.3 and
ASCs are shown in Figure 4.4.
Figure 4.3 Rail Mounted Gantries
Figure 4.4 Automatic Stacking Cranes (no driver)
Due to the need to travel a long distance (few hundreds meters) and handle the
heavy containers that is drawing large current over a long cable, these machines are
electrical powered at high voltage level and the drive system can either be an AC
drive system or a DC drive system. Unless specified, all machines are now come
with AC drive system simply because they can operate at or close to unity power
factor.
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47
It was not able to record load profiles for RMG or ASC as the Melbourne Container
Terminal does not have any of these machines. However, it was expected the load
profiles of RMG and ASC are very similar to that of the quay cranes as:
x Hoist/Lower motion would be similar as the container loads are the same for
these machines,
x The long travel motion would be the predominant one as RMGs and ASCs
need only hoist/lower a short distance but long travel a very long distance.
x Demand and energy usage are also less than that of the quay crane due to the
nature of the long travel motion overcome friction rather than lifting a
weight.
The Melbourne Container Terminal has both AC drive and DC drive quay cranes.
With the permission from the management team, load profile of these quay cranes
were obtained as described in next section.
4.2 Load Profiles of Quay Crane Comparison between AC and DC drive systems
Since the introduction of IGBT based AC drive products in the late 1980s, there has
been much debate on which technology AC or DC drive should be used by the
crane industry for new container cranes. The AC technology appears to win the
debate as today almost all container cranes are AC. However, the electrical power
demand and energy usage of container cranes have not been mentioned in any
debate. With the new bigger and faster container cranes being built, the high
electrical cost of running these container cranes must now be closely analysed.
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With the permission of management team of Melbourne Container Terminal, load
profiles of two very similar quay cranes one with AC drive system and the other
with DC drive system - had been obtained on 29 January 2008 and 13 February
2008. As described in chapter 3, the Schneider circuit monitor CM3250 was used at
the high voltage supply end of each quay crane to capture the electrical data every
second then uploaded to the Energy Management System data base. The operation
data (time, container number, weight, quay crane motion, load or unload) were also
recorded for analysis. Details were discussed below.
4.2.1 AC and DC quay cranes under study
As there were no exactly match pair of quay cranes at the container terminal, two
very similar quay cranes (physical size, mechanical arrangement, year of
manufactured) had to be selected to produce comparable results.
Almost only Hoist and Cross Travel motions are used in loading/unloading
containers to/from container ship. These motions produce the peak demand and
around 99% of the energy usage. Therefore, this study concentrated mainly on these
two motions. The main electrical data of these quay cranes was listed in Table 4.1.
Table 4.1 Main data of Quay cranes under observation
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The AC quay crane uses AC drive system with Active Front End technology that is
full compensation can be made for power factor and harmonics. The DC quay crane
uses DC drive technology with harmonic filter to compensate the generated
harmonics.
4.2.2 Study results
It was expected the peak demand would be larger for AC drive technology due to
the fact that:
x the AC motor size that have to be larger in size to produce the same torque
and overload capability resulting in. larger rotational inertial, cooling
systems and power consumption,
x the AC drives technology requires two steps, conversion and inversion while
DC drive technology needs only conversion. This means extra power
requirement, larger cooling devices as more heat would be generated for the
AC drives.
Electrical data were captured during actual working conditions: loading containers
to container ship. At the same time, loading sequence and container weight are also
recorded. Figure 4.5 and Figure 4.6 show graph of Real Power (kW), Reactive
Power (kVAr) and Apparent Power (kVA) of the quay cranes working on the same
ship hold, ie. minimum usage of gantry motion.
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N:
N9$UN9$
Figure. 4.5 AC quay crane Graph of powers vs. time (second).
N:
N9$U
N9$
Figure 4.6 DC quay crane Graph of powers vs. time (second).
The first impression is that DC quay crane handled more containers, there are
regenerative Real Power (-ve kW), DC quay crane requires larger kVA demand.
This data is used to calculate the energy usage of the quay crane for handling each
container.
To make comparison, a loading cycle with the similar container weight and similar
travel distances are used. Figure 4.7 and Figure 4.8 show the Power graphs of the
AC and DC quay cranes when handling container weight 26.1T and 26T
respectively.
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N:
N9$U
N9$
Figure 4.7 AC quay crane Graph of powers vs. time (second) for one loading
cycle.
N:
N9$U
N9$
Figure 4.8 DC quay crane Graph of powers vs. time (second) for one loading cycle.
A loading cycle comprises of::
- Lock the container to the spreader for a safe move,
- Hoist the container up, start cross travel (while hoisting) to sea side when clear of all obstacles,
- Lower the container to its final position and unlock,
- Hoist the empty spreader up, start cross travel (while hoisting) to land side when clear of all obstacles,
- Lower the empty spreader on top of the next container.
Therefore a graph of Power versus Time of a complete load cycle was expected to
have four peaks values. The Real Power should have two negative peaks
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(regenerative when lowering). Figure 4.7 and Figure 4.8 confirmed these
expectations. The slightly differences in shape and duration were due to the
techniques of the quay crane drivers.
Peak Power Demand and Energy Usage
The results were summarised in Table 4.2. Theoretical average power demands
were calculated and also shown in the table for reference only. The formula were
from chapter two and actual mechanical data used in calculation of the average
demand would be shown in later section. To make a true comparison between AC
and DC quay cranes, the electrical conditions had to be the same. It was assumed
that the issue of poor power factor of DC drive quay crane was not a concern;
comparison was now based on the peak kW demand rather than the peak kVA
demand.
As shown in Table 4.2, peak demand from AC quay crane was 21.9% higher than
DC quay crane. When taking the Safe Working Load of the quay cranes into
account, the difference was still expected to be higher than 15%.
As discussed in Chapter 3, the Electrical Distribution Company (the Utility) does
not look at this instantaneous peak/maximum demand. The peak/maximum demand
was normally calculated from the remotely read energy kWHr and kVArHr every
15 or 30 minutes. That means the peak kW demand shown in the electrical bill was
actual the average kW demand.
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Table 4.2 Results of measurement
Quay Crane with AC Drive DC Drive Differences Load condition Number of loads 29 47 Load Weights From 7T to 48.4T From 7T to 48.4T Results Net used energy (kWHr) 113.50 115.20 Average used energy per 3.91 2.45 For 26T load Peak demand (kW) 1476 1211 21.88% Average demand (kW) 147.75 105.26 40.37% Cal. Ave. demand (kW) 152.01 126.83 19.85% Power factor - Real time 0.087 1 0.006 - 0.838 Power factor - calculated 0.952 0.475 Total Harmonic Distortion (THD) Line Current Ia (%) 1.9 - 51.9 5.6 - 49.7 Ib (%) 1.6 - 830.3 5.3 - 56.9 Ic (%) 1.6 - 93.1 63. -50.9 Line Voltage Vab (%) 0.9 - 1.2 0.7 - 1.9 Vbc (%) 0.9 - 1.2 0.8 - 2.0 Va (%) 0.9 - 1.2 0.6 - 1.8
For 26T container load, the AC quay crane kW demand was 40% higher. Taking
into account the drivers techniques, the final position of the container and other
containers on the ship, the difference was still expected to be in the low 20%.
With higher peak and average demand, the energy usage had to be higher for AC
drive quay crane. An average of 60% more energy was required to handle a
container during this observation. AC drive quay crane used 100% more energy
than DC drive quay crane had been observed at other time.
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Power Factor
Figure 4.9 and Figure 4.10 show graph of Power Factor vs. Time of AC and DC
drive quay cranes when handling 26T container and the numerical results were
shown in Table 4.2. An average Power Factor was also shown in the graphs. This
average Power Factor (as seen by the Utility) was the ratio of kWHr and kVAHr.
3RZHU)DFWRU$YHUDJH3)
Figure 4.9 AC quay crane Graph of power factor vs. time (second) for one
loading cycle.
3RZHU)DFWRU$YHUDJH3)
Figure 4.10 DC quay crane Graph of power factor vs. time (second) for one
loading cycle.
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55
As expected, DC drive quay crane had a very poor power factor. However, it is
possible to solve this problem by using a dynamic power factor correction unit. A
dynamic power factor correction unit consists of capacitor banks and power
electronic switches. A microprocessor is used to control the switching to connect an
appropriate amount of corrective capacitance on the per-cycle basic (50 cycles
per second for 50Hz system) [55, 56]. The desired power factor can easily be
achieved.
Crane Factor from TM GE Automation system or Pure wave AVC from S and
C Electric Company are two examples of such unit.
The Melbourne Container Terminal used a Pure Wave AVC unit with a very good
result. For better utilization, the power factor correction unit was connected at the
main 11kV bus bar, which supplied three (3) DC drive quay cranes, two (2) AC
drive quay cranes and 500 outlets for refrigerated containers. Overall power factor
is always greater than 0.9.
So that with the right selection of equipment, poor power factor of DC drive quay
crane was no longer an issue.
Total Harmonic Distortion (TDH)
Measured TDHs of live voltage and current for AC and DC drive quay cranes
during the 26T loading cycle were plotted against time (second) as shown in Figure
4.11 and Figure 4.12. Different scales were used for voltages and currents.
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56
,D
,E
,F
9DE
9EF
9FD
Figure 4.11 AC quay crane Graph of THD (%) vs. time (second) for one
loading cycle.
,D
,E
,F
9DE
9EF
9FD7+' /LQH
Figure 4.12 DC quay crane Graph of THD (%) vs. time (second) for one
loading cycle.
The measurement shown an abnormal THD value of 830.3% of current on phase b.
AC drive quay crane achieves smaller variation of THDs of voltages and currents.
However, THDs of both AC and DC drive quay cranes were comparable.
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57
4.2.3 Study conclusions
With observation and actual measured electrical data of quay cranes with AC drive
and DC drive systems, load profiles of these quay cranes were studied and
understood. It could be concluded that if proper power factor correction and
harmonic compensation were provided, a quay crane with DC drive technology was
a better choice as it produced lower Peak Demand and Energy Usage. However, this
conclusion was simply based on the electrical point of vi