A Modular Framework for Optimizing Grid Integration of Mobile and Stationary Energy Storage in Smart Grids

224 Pages·2019·2.226 MB·English

by  Dominik Pelzer

Dominik Pelzer
A Modular Framework
for Optimizing Grid
Integration of Mobile
and Stationary Energy
Storage in Smart Grids
A Modular Framework for Optimizing
Grid Integration of Mobile and Stationary
Energy Storage in Smart Grids
Dominik Pelzer
A Modular Framework
for Optimizing Grid
Integration of Mobile
and Stationary Energy
Storage in Smart Grids
Dominik Pelzer
Hamburg, Germany
Dissertation TU München, Germany, 2018
ISBN 978-3-658-27023-0 ISBN 978-3-658-27024-7 (eBook)
https://doi.org/10.1007/978-3-658-27024-7
Springer Vieweg
© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole
or part of the material is concerned, specifically the rights of translation, reprinting, reuse of
illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way,
and transmission or information storage and retrieval, electronic adaptation, computer software,
or by similar or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this
publication does not imply, even in the absence of a specific statement, that such names are
exempt from the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in
this book are believed to be true and accurate at the date of publication. Neither the publisher
nor the authors or the editors give a warranty, expressed or implied, with respect to the material
contained herein or for any errors or omissions that may have been made. The publisher remains
neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This Springer Vieweg imprint is published by the registered company Springer Fachmedien Wiesbaden
GmbH part of Springer Nature
The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany
Table of Contents
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Approach . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . 7
1.4 Scope of This Work. . . . . . . . . . . . . . . . . . . . 10
1.5 Organization of This Work . . . . . . . . . . . . . . . 11
2 The Big Picture: Smart Grids, Electricity Markets, En-
ergy Storage Systems and Electric Vehicles 13
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 Smart Grids . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2.1 Demand-Side Management and Energy Stor-
age Systems . . . . . . . . . . . . . . . . . . . . 14
2.2.2 Control Paradigms . . . . . . . . . . . . . . . . 16
2.3 Electricity Markets . . . . . . . . . . . . . . . . . . . . 18
2.3.1 Market Operators . . . . . . . . . . . . . . . . 19
2.3.2 Market Types and Service Classes . . . . . . . 19
2.3.3 Pricing Schemes . . . . . . . . . . . . . . . . . 22
2.4 Energy Storage . . . . . . . . . . . . . . . . . . . . . . 24
2.4.1 Battery Technologies . . . . . . . . . . . . . . . 25
2.4.2 SuitabilityofBatteryEnergyStorageSystems
for the Different Services and Markets . . . . . 27
2.4.3 Drivers for the Market Development of Bat-
tery Energy Storage Systems . . . . . . . . . . 28
2.5 Plug-In Electric Vehicles . . . . . . . . . . . . . . . . . 29
2.5.1 Market Aspects . . . . . . . . . . . . . . . . . . 29
2.5.2 Power Grid Impact . . . . . . . . . . . . . . . . 30
2.6 Grid Integration of Battery Energy Storage Systems
and Plug-In Electric Vehicles . . . . . . . . . . . . . . 35
2.6.1 Classification of Coordination Approaches . . . 35
vi Table of Contents
2.6.2 Profitability of Battery Energy Storage Sys-
tems for Power Grid Services . . . . . . . . . . 37
2.6.3 Battery Degradation Monetization . . . . . . . 40
2.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 41
3 Framework Architecture 45
3.1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2 Framework Overview . . . . . . . . . . . . . . . . . . . 47
3.3 Components . . . . . . . . . . . . . . . . . . . . . . . . 51
3.4 Interactions . . . . . . . . . . . . . . . . . . . . . . . . 63
3.5 Transportation and Power System Simulation . . . . . 64
3.5.1 CityMoS Traffic . . . . . . . . . . . . . . . . . . 64
3.5.2 CityMoS Power . . . . . . . . . . . . . . . . . . 67
3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 70
4 Scheduling Approach 73
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 73
4.2 Multi-StageOptimizationProblemwithRollingHorizon 74
4.2.1 Formulation as Dynamic Programming Problem 77
4.2.2 Solution Algorithm . . . . . . . . . . . . . . . . 78
4.3 Equivalent Circuit Model . . . . . . . . . . . . . . . . 79
4.3.1 Reference Cell and Test Cell. . . . . . . . . . . 80
4.3.2 Open Circuit Voltage. . . . . . . . . . . . . . . 81
4.3.3 Internal Resistance . . . . . . . . . . . . . . . . 83
4.4 Charging Model . . . . . . . . . . . . . . . . . . . . . . 87
4.4.1 Linear Model . . . . . . . . . . . . . . . . . . . 88
4.4.2 EquivalentCircuitModel-BasedChargingModel 88
4.5 Battery Degradation Monetization Model . . . . . . . 94
4.5.1 Battery Degradation Processes . . . . . . . . . 94
4.5.2 Basic Model Assumptions . . . . . . . . . . . . 96
4.5.3 Physical Degradation Formalization . . . . . . 98
4.5.4 End of Life Estimation . . . . . . . . . . . . . . 102
4.5.5 Computing State of Health . . . . . . . . . . . 103
4.5.6 Degradation Monetization . . . . . . . . . . . . 104
Table of Contents vii
4.5.7 Degradation Model Parametrization . . . . . . 105
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 106
5 Applications 109
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 109
5.2 General Parameters . . . . . . . . . . . . . . . . . . . 109
5.3 Understanding the Implications of the Degradation
Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
5.3.1 Capacity Loss and the Influence of Calendar
and Cycle Degradation on Costs . . . . . . . . 111
5.3.2 Dependency of Degradation Costs on Other
Battery Parameters . . . . . . . . . . . . . . . 119
5.3.3 Conclusion . . . . . . . . . . . . . . . . . . . . 121
5.4 Parameter Sensitivity . . . . . . . . . . . . . . . . . . 123
5.4.1 General Parameters . . . . . . . . . . . . . . . 123
5.4.2 Results . . . . . . . . . . . . . . . . . . . . . . 123
5.4.3 Conclusion . . . . . . . . . . . . . . . . . . . . 130
5.5 Comparison of Charging Strategies in a Singapore
Context . . . . . . . . . . . . . . . . . . . . . . . . . . 131
5.5.1 Data and Parameters. . . . . . . . . . . . . . . 133
5.5.2 Determining Battery Capacity . . . . . . . . . 135
5.5.3 Results . . . . . . . . . . . . . . . . . . . . . . 136
5.5.4 Conclusion . . . . . . . . . . . . . . . . . . . . 143
5.6 Economic Viability of Battery Energy Storage Sys-
tems in Different Markets . . . . . . . . . . . . . . . . 146
5.6.1 Markets . . . . . . . . . . . . . . . . . . . . . . 147
5.6.2 Parameters . . . . . . . . . . . . . . . . . . . . 147
5.6.3 Results . . . . . . . . . . . . . . . . . . . . . . 148
5.6.4 Conclusion . . . . . . . . . . . . . . . . . . . . 156
5.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 158
6 Conclusion 161
6.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . 161
6.1.1 Methodology . . . . . . . . . . . . . . . . . . . 161
viii Table of Contents
6.1.2 Results . . . . . . . . . . . . . . . . . . . . . . 163
6.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . 167
6.2.1 Extending the Framework’s Range of Appli-
cation . . . . . . . . . . . . . . . . . . . . . . . 167
6.2.2 DevelopmentTowardsaSchedulingMechanism
Integrated in Battery Management Systems . . 170
6.2.3 Extended Degradation Models . . . . . . . . . 173
6.2.4 Business Models for Battery Energy Storage
Systems . . . . . . . . . . . . . . . . . . . . . . 174
Bibliography 177
Publications 205
List of Figures
2.1 Basic load shaping techniques. . . . . . . . . . . . . . 16
2.2 Simulation results showing the impact of PEV charg-
ing on the Singapore power grid. . . . . . . . . . . . . 33
3.1 Pricedatabaseschemecontainingtherequiredmarket
information. . . . . . . . . . . . . . . . . . . . . . . . . 50
3.2 Framework architecture overview. . . . . . . . . . . . . 51
3.3 Overviewoftheclassesofthemodulesstorage_system,
storage_unit and storage_commitment. . . . . . . . . 59
3.4 Conceptualized sequence diagram. . . . . . . . . . . . 65
4.1 Measured OCV data and fit function. . . . . . . . . . 82
4.2 Illustration of ohmic resistance. . . . . . . . . . . . . . 84
4.3 Charge polarization voltage of the test cell. . . . . . . 86
4.4 Comparison between measured data and fit functions. 87
4.5 Illustrationofcalendarandcyclecapacitylossfortwo
cycling regimes. . . . . . . . . . . . . . . . . . . . . . . 99
5.1 Various model output parameters for a sequence of
two different cycling regimes. . . . . . . . . . . . . . . 113
5.2 Calendar and cycle capacity loss as a function of time
for two different cycling regimes. . . . . . . . . . . . . 114
5.3 Comparison of various model outputs for two investi-
gated scenarios with two cycling regimes. . . . . . . . 115
5.4 Degradationcostsandcontributionofagingprocesses
to overall degradation for different state transitions. . 116
5.5 Calendar costs per hour for 20kWh of battery capac-
ity at different temperatures. . . . . . . . . . . . . . . 118
5.6 Average degradation costs considering calendar and
cycle aging by varying battery price, battery capacity
and the EOL condition. . . . . . . . . . . . . . . . . . 120
x List of Figures
5.7 ΔΓ dependency of calendar and cycle costs in a
EOL
log-log plot. . . . . . . . . . . . . . . . . . . . . . . . . 120
5.8 Sensitivity with regard to solver settings. . . . . . . . 127
5.9 Sensitivity with regard to fundamental battery spec-
ifications. . . . . . . . . . . . . . . . . . . . . . . . . . 128
5.10 Profits as a function of various battery operation pa-
rameters. . . . . . . . . . . . . . . . . . . . . . . . . . 129
5.11 Cumulativeshareofthepopulationaccordingtodaily
energy consumption. . . . . . . . . . . . . . . . . . . . 136
5.12 Share of agents as a function of their relative savings
with smart charging in the year 2017. . . . . . . . . . 140
5.13 Comparison of ICEV and PEV operating costs for
different itineraries with uncoordinated charging and
smart charging. . . . . . . . . . . . . . . . . . . . . . . 142
5.14 Share of agents with cost-competitiveness of PEVs
with ICEVs for different battery capacities in the un-
coordinated charging scenario. . . . . . . . . . . . . . . 143
5.15 Average annual profits with a lookahead of 7. . . . . . 149
5.16 Averageannualprofitscomputedconsideringcalendar
and cycle aging with a lookahead of 7. . . . . . . . . . 150
5.17 Average annual profits over time in the different NY-
ISO zones for a battery price of $150 per kWh. . . . . 153
5.18 Arbitrage profits for time resolutions of 5min and
60min with a lookahead of 7 for the year 2015. . . . . 155
5.19 Average annual profits for Γ = 0.6. . . . . . . . . . 157
EOL