Electricity Markets (eBook)

Preface 5
Contents 6
About the Editors 8
1 Energy Harvesting Technologies and Market Opportunities 9
Nomenclature 9
1.1 Introduction 10
1.2 Energy Harvesting Technologies and Challenges 10
1.3 Energy Harvesting Markets and Key Players 11
1.4 Intelligent Mechanisms for Energy Harvesting 14
1.5 Conclusions and Suggested Readings 21
References 23
2 Electricity Market Pricing: Uniform Pricing vs. Pay-as-BidPricing 27
2.1 Introduction 27
2.2 Contributions 29
2.3 Electricity Market Pricing 29
2.3.1 Vickrey–Clarke–Groves (VCG) 29
2.3.2 Uniform Price Auction 30
2.3.2.1 The Advantages with the UPA 31
2.3.2.2 The Disadvantages with the UPA 32
2.3.3 Pay-as-Bid Auction 32
2.3.3.1 The Advantages with PABA 35
2.3.3.2 The Disadvantages with PABA 35
2.4 Switching from UPA to PABA? 36
2.5 Conclusion 40
References 41
3 Integrated Gas and Power Networks 44
Nomenclature 44
Sets 44
Parameters 44
Variables 45
3.1 Introduction 47
3.2 Expansion Co-planning of Electricity and Gas Networks 49
3.3 Operational Co-planning of Electricity and Gas Networks 59
3.4 Conclusion 65
References 66
4 Transmission Pricing: Right Insights for Suitable Cost Allocation Methods 68
4.1 Introduction 68
4.2 Transmission Pricing in Modern Electric Power Systems 69
4.2.1 Energy Transition Ongoing 70
4.2.1.1 Major Changes and Repercussions 70
4.2.1.2 How the Energy Transition Impacts on the TCA Paradigm 72
4.2.1.3 Integration of Devices and Systems 73
4.2.1.4 How the Power Sector Integration Trend May Be Captured by TCA Methods 75
4.2.1.5 Outlook over Selected Transmission Systems 76
4.2.2 Transmission Fundaments 77
4.2.2.1 Economics and Regulation 77
4.2.2.2 Principles to Allocate the Costs 78
4.2.2.3 Requirements to Develop Algorithms 80
4.2.2.4 The Ideal TCA Method 81
4.3 Transmission Cost Allocation Methods: Review and Analysis 81
4.3.1 Relevant Publications 83
4.3.1.1 Power Flow Based 83
4.3.1.2 Incremental Cost 84
4.3.1.3 Marginal Cost 84
4.3.1.4 Alternative Strategies 84
4.3.1.5 Newfound Approaches 86
4.3.2 Literature: Broad Findings 86
4.3.3 Publications with the Most Suitable Features 87
4.4 Conclusions and Future Directions 90
References 91
5 Quantifying the Effect of Autonomous Demand Response Program on Self-Scheduling of Multi-carrier Residential Energy Hub 98
Nomenclature 98
Sets and Indices 98
Parameters 98
Variables 100
Functions 100
5.1 Introduction 100
5.2 Energy Hub 103
5.3 Problem Formulation 104
5.3.1 Component Modelling 106
5.3.1.1 Energy Storage 106
5.3.1.2 CHP Unit 107
5.3.1.3 Solar Panel 109
5.3.1.4 Load Modelling 109
5.3.1.5 Uncertainty Modeling 111
5.3.1.6 Heat and Power Balance 112
5.3.1.7 Objective Function 112
5.4 Numerical Results 113
5.4.1 Data 113
5.4.2 Results 114
5.5 Conclusion 117
References 118
6 Offering Strategy of Thermal-Photovoltaic-Storage Based Generation Company in Day-Ahead Market 120
6.1 Introduction 120
6.2 Uncertainty Modeling 122
6.3 Problem Formulation 124
6.3.1 Objective Function 124
6.3.2 Emission Constraint 125
6.3.3 CVaR Constraints 126
6.3.4 Imbalance Constraints 126
6.3.5 BSS Constraints 127
6.3.6 Thermal Units Constraints 127
6.3.7 PV System Constraints 129
6.3.8 Offering Curves Constraints 129
6.4 Numerical Results 130
6.4.1 Input Data 130
6.4.2 Simulation Results 130
6.5 Conclusion 133
Nomenclature 137
Indices 137
Constants 138
Variables 138
References 139
7 Risk-Based Purchasing Energy for Electricity Consumers by Retailer Using Information Gap Decision Theory Considering Demand Response Exchange 141
Nomenclature 141
Parameters 141
Numbers 142
Variables 142
Functions 142
7.1 Introduction 143
7.1.1 Literature Review 143
7.1.2 Novelty and Contributions 145
7.1.3 Chapter Organization 148
7.2 Problem Formulation 149
7.2.1 Objective Function and Power Balance Constraint 149
7.2.2 Wholesale Market Suppliers 149
7.2.2.1 Pool Market 150
7.2.2.2 Forward Contract 150
7.2.3 Pool-Order Option 151
7.2.4 Forward DR 152
7.2.5 Reward-Base DR 153
7.3 IGDT Technique 154
7.3.1 System Model 154
7.3.2 Operation Requirements 154
7.4 Proposed IGDT-Based Risk-Constraint Formulation 155
7.4.1 Uncertainty Modeling 155
7.4.2 Robustness Function (Risk-Averse Strategy) 156
7.4.3 Opportunity Function (Risk-Taker Strategy) 157
7.4.4 Base Function (Risk-Neutral Strategy) 158
7.5 Proposed Algorithm for Obtaining Optimal Bidding Strategy 158
7.6 Case Study 159
7.6.1 Risk-Neutral Results Without IGDT 162
7.6.2 Robustness and Opportunity Functions 163
7.6.3 Optimal Bidding Strategy Result 165
7.6.4 Comparison of Risk-Based Results 166
7.6.4.1 Analysis Results of Proposed DR Schemes 166
7.6.4.2 Analysis Results of Wholesale Market Suppliers 168
7.7 Conclusion 169
References 171
8 Stochastic Cooperative Charging Scheduling of PEV Fleets in Networked Microgrids Considering Price Responsive Demand and Emission Constraints 175
8.1 Introduction 175
8.1.1 Motivation 175
8.1.2 Literature Review 178
8.1.3 Contributions 180
8.1.4 Chapter Organization 181
8.2 Incentive-Based DR Programs 182
8.2.1 Concepts 182
8.2.2 Modeling 184
8.3 Electric Vehicle 185
8.3.1 Aim 185
8.3.2 Stages of EV Development 186
8.3.3 Classification of EVs 186
8.3.4 V2G Technology 187
8.4 Problem Formulation 189
8.4.1 Objective Function 189
8.4.1.1 Total Cost Function 189
8.4.1.2 Operation Cost of DGRs 190
8.4.1.3 Operation Cost of PEVs 190
8.4.1.4 Cost of Greenhouse Gas Emission 190
8.4.2 Constraints 191
8.4.2.1 Power Mismatch Constraint 191
8.4.2.2 Lines Limit 192
8.4.2.3 Limit of Power Flow in the Lines 192
8.4.2.4 Under/Over Voltage Limits 192
8.4.2.5 PEVs Limitations 192
8.4.2.6 DGRs Constraints 193
8.5 Scenario Modeling 193
8.6 Simulation Results 194
8.6.1 Data and Case Study 194
8.6.2 Numerical Results 197
8.7 Conclusion 200
References 201
9 Robust Scheduling of Plug-In Electric Vehicles Aggregator in Day-Ahead and Reserve Markets 204
Nomenclature 204
Set 204
Parameters 204
Numbers 205
Variables 205
9.1 Introduction 205
9.2 Deterministic-Based Scheduling of PEV Aggregator 207
9.3 Robust Optimization-Based Scheduling of PEV Aggregator 209
9.4 Case Study 211
9.5 Conclusion 216
References 216
10 Optimal Scheduling of Water Distribution Systems' Participation in Demand Response and Frequency Regulation Services 218
10.1 Introduction 218
10.2 Problem Formulation 219
10.3 Robust Optimization Approach 220
10.4 Water Distribution System Model 221
10.5 Case Study 225
10.6 Conclusion 232
References 232
11 Optimal Power Scheduling of a GenCo Using Two-Point Estimate Method 234
Nomenclature 234
Set 234
Known Parameters 234
Decision Variables 235
Functions 235
11.1 Introduction 235
11.2 Deterministic-Based Scheduling of a GenCo 236
11.3 Background of TPEM 238
11.4 Numerical Study 240
11.5 Comparison and Discussion 248
11.6 Conclusion 249
References 249
12 Bidding and Offering Strategies for Integration of Battery Storage System and Wind Turbine 252
Nomenclature 252
Indices 252
Input 252
Variables 253
12.1 Introduction 253
12.2 Problem Formulation 255
12.2.1 Objective Function 256
12.2.2 WT Model 256
12.2.3 BSS Model 257
12.3 Numerical Simulation 258
12.4 Conclusion 263
References 264
Index 267