Demand Response in Smart Grids

This book is the first of its kind to comprehensively describe the principles of demand response. This allows consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage in response to the grid reliability need, time-based rates or other forms of financial incentives. The main contents of the book include modeling of demand response resources, incentive design, scheduling and dispatch algorithms, and impacts on grid operation and planning. Through case studies and illustrative examples, the authors highlight and compare the advantages, disadvantages and benefits that demand response can have on grid operations and electricity market efficiency. First book of its kind to introduce the principles of demand response; Combines theory with real-world applications useful for both professionals and academic researchers; Covers demand response in the context of power system applications. Preface 6 Contents 10 Chapter 1: Overview of Demand Response 16 1.1 Introduction 16 1.2 History of Demand Responses in North America 17 1.3 Benefits of Demand Responses 18 1.3.1 Peak Load Reduction 19 1.3.2 Congestion Management in Distribution Network 20 1.3.3 Ancillary Service (AS) 21 1.3.4 Emergency Conditions and Prevention of Blackouts 23 1.3.5 Transactive Control with Continuous Response to System Imbalance 24 1.4 Motivations and Barriers for Implementing Demand Responses 25 1.5 Demand Response Control 26 1.5.1 Interruptible Loads 27 1.5.2 Direct Load Control (DLC) 27 1.5.3 Time of Use (TOU)/Critical Peak Pricing (CPP)/Critical Peak Rebate (CPR) 28 1.5.4 Real-Time Price (RTP) 28 1.5.5 Controllable Load as Resources (CLR) 29 1.6 Demand Responses in Wholesale Market 29 1.6.1 Overview 30 1.6.1.1 Demand Response in Energy Market 30 1.6.1.2 Demand Response in Ancillary Service Market 30 1.6.1.3 Demand Response in Capacity Market 31 1.6.2 Demand Responses in North American Markets 33 1.6.2.1 ERCOT 33 1.6.2.2 PJM Interconnection 33 1.6.2.3 MISO 34 1.6.2.4 ISO New England (ISO-NE) 35 1.7 Lessons Learned and Outlook 36 1.7.1 Lessons Learned 37 1.7.2 Changes for Future Grid to Enable High DR Participations 38 1.7.2.1 Market Rules 38 1.7.2.2 Price Formulation 39 1.7.2.3 Coordination between DRs to Reduce ``Paid Back ́ ́ Energy 40 1.8 Summaries 41 References 42 Chapter 2: Modeling Demand Response Resources 43 2.1 Thermal Characteristics of the TCL 43 2.2 First-Principle-Based Approach 44 2.3 Measurement-Based Approach 48 2.3.1 Simplified RCQ Model 49 2.3.2 Linearized ETP Model 51 2.4 Error Correction by Measurement 52 2.5 Parameter Randomization 56 2.6 Modeling Non-thermostatically Controllable Loads 59 2.7 Modeling the Base Load 62 References 64 Chapter 3: Basic Control Approach for Aggregated Demand Response Programs 65 3.1 Direct Load Control Algorithms 65 3.1.1 General Design Considerations 65 3.1.2 Test System Setup 66 3.1.3 Test System Initialization 68 3.1.4 Construction of Operation Baseline 68 3.1.5 Construction of the Control Signal 69 3.1.6 Priority-List-Based HVAC Control Algorithm 70 3.1.6.1 No-Controlled Case 72 3.1.6.2 Baseline Case 73 3.1.6.3 Load Following Case 74 3.1.7 Performance for Providing Load Following Services 76 3.2 Indirect Load Control Algorithms 80 3.2.1 Response Curves 80 3.2.2 ILC-Based Demand Response under TOU Price 82 3.2.3 ILC-Based Demand Response under the Critical-Peak Price 85 3.3 Autonomous Load Control Algorithm 87 3.3.1 Statistics of Raw Frequency Data 88 3.3.2 Frequency-Responsive Appliance Design Considerations 89 3.3.3 Triggering Statistics of an ACFR Load 92 3.4 Summary 96 References 97 Chapter 4: Demand Responses in ERCOT 99 4.1 Introduction 99 4.2 Overview of ERCOT 100 4.3 ERCOT Market Structure 100 4.3.1 Ancillary Services (AS) 101 4.3.2 The Day Ahead Energy Market 102 4.3.3 The Real-Time Market 102 4.4 Overview of Demand Response Options in ERCOT 102 4.4.1 Non-ERCOT-Dispatched DR 103 4.4.1.1 Four Coincident Peak (4CP) 104 4.4.1.2 LSE Contracted Price Response 104 4.4.1.3 Self-Directed Price Response 104 4.4.1.4 Transmission and Distribution Utility Commercial Load Management (CLM) Programs 105 4.4.2 ERCOT-Dispatched Demand Response 105 4.4.2.1 Emergency Response Service (ERS) 105 4.4.2.2 Ancillary Services Markets 106 Responsive Reserve Service (RRS) 107 Non-Spinning Reserve Service (Non-Spin) 108 Up-Regulation Service and/or Down-Regulation Service 108 4.4.3 Real-Time Energy Market 108 4.5 Load Resources Providing RRS 108 4.6 ERCOT Emergency Response Service (ERS) 114 4.6.1 ERS History and Requirement 114 4.6.2 Capacity Demand Curve 115 4.6.3 Baselines for ERS Loads 120 4.6.3.1 Default Baseline 121 4.6.3.2 Alternate Baseline 122 4.7 Load in SCED 123 4.7.1 Benefits of Load Participation in the Real-Time Market 124 4.7.2 Eligibility of Loads in SCED 124 4.7.3 Modifications to SCED 125 4.7.3.1 Mathematical Formulation of SCED 125 4.7.3.2 Solving SCED Problem 126 4.7.4 Compensation of Demand Response in the Energy Market 127 4.7.4.1 Option 1: Settlement Concept: LMP minus LMPz 128 4.7.4.2 Option 2: Alternative Approach: Full LMP 128 4.7.5 Performance of SCED Dispatch for Load 129 4.8 Summary 130 Further Reading 133 Chapter 5: Integrated Demand Response in the Multi-Energy System 134 5.1 Introduction 134 5.2 Concept of Integrated Demand Response 135 5.2.1 The Basic Concept of IDR 135 5.2.2 The Value Analysis of IDR 137 5.3 Improve the Economy of Energy Systems 138 5.4 Enhance the Reliability of Energy Systems 138 5.5 Exploit the Capability of Demand Side Resources 138 5.5.1 The Techno-Economic Analysis of IDR 139 5.6 IDR Research in the Multi-Energy System 140 5.6.1 Modeling 140 5.6.2 Operation Strategy 142 5.6.3 Market Behavior 143 5.7 IDR Application in the Multi-Energy System 144 5.7.1 The USA 145 5.7.2 Europe 145 5.7.3 China 146 5.8 Key Issues and Potential Researches of IDR 147 5.9 The Precise Modeling of Multi-Energy Consumption 147 5.10 The Scheduling Strategy for MESs with IDR Considering the Influences of Different Energy Prices 148 5.11 The Data-Driven Consumption Strategy of IDR 149 5.12 The Market Operation and Mechanism Design Considering IDR 149 5.13 Conclusion 150 References 151 Future Reading 155 Chapter 6: Coupon Incentive-Based Demand Response 156 6.1 Introduction 156 6.2 The CIDR Formulation 159 6.2.1 Information Exchange Scheme 159 6.2.2 Timeline of CIDR 160 6.2.3 Choice of Consumer Baselines 161 6.2.4 ISO/RTO 162 6.2.5 LSE 163 6.2.6 Consumer 163 6.2.7 Adjustment of the Coupon Price 164 6.2.8 Comparisons with the PTR/CPP (Critical Peak Pricing) 165 6.3 Critical Assessment of CIDR 166 6.3.1 Consumer Surplus 167 6.3.2 LSE Profit 168 6.3.3 Social Welfare 168 6.3.4 Robustness of the Retail Rate 169 6.3.5 Readiness for Implementation 169 6.3.6 Pros and Cons 170 6.4 Numerical Case Study 171 6.4.1 Scenario Without the Iteration Between LSEs and Consumers 174 6.4.2 Impact of the Consumer Participation Rate 175 6.5 Conclusion 175 References 176 Chapter 7: Distributed Real-Time Demand Response 179 7.1 Introduction 179 7.1.1 Motivation 179 7.1.2 Literature Review and Contribution 180 7.2 Real-Time Demand Response Model 181 7.2.1 Objective 182 7.2.2 Constraints 183 7.3 Lagrangian Relaxation Approach 184 7.4 Sensitivity Analysis 185 7.4.1 General Sensitivity Expressions 186 7.4.2 Objective Sensitivity 187 7.4.3 Variable Sensitivity 188 7.5 Lagrangian Multiplier Optimal Selection Approach 189 7.6 Case Studies 192 7.6.1 Utility Functions Analysis 192 7.6.2 Smart Distribution Grid with 10 Consumers 193 7.6.3 Smart Distribution Grid with 100 Consumers 196 7.6.4 Real-World Distribution Grid with 14 Commercial Consumers 198 7.7 Conclusions 199 Appendix 201 Variable Sensitivity Simplification 201 Convergence Analysis 202 References 203 Chapter 8: Load Resources to Provide Primary Frequency Reserve Service 206 8.1 Introduction of Frequency Control 206 8.2 Impact of Renewable Resource over Inertia and Primary Frequency Control 208 8.3 Frequency Response Reserves at ERCOT 209 8.4 Quantification of FRR Requirement 212 8.4.1 Step 1: Selection of Representative Operation Conditions 213 8.4.2 Step 2: Setup of Dynamic Models 214 8.4.3 Step 3: Quantification of Minimum FRR Requirement 214 8.4.4 Step 4: Derivation of Equivalency Ratio for All Cases 215 8.5 Co-optimization of Energy and FRR in Day-ahead Market 217 8.5.1 Day-ahead market co-optimization model 217 8.5.2 Solution of day-ahead market co-optimization 222 8.5.3 Case Studies 224 8.6 Co-optimization of Energy and FRR in Real-time 230 8.6.1 Problem Formulation 231 8.6.2 Pricing Strategy 233 8.6.3 FFR ́s Market Behaviors 234 8.6.3.1 Base Case 234 8.6.3.2 Mitigation of Price Spikes at the PFC Market 236 8.7 Conclusions 238 References 239 Chapter 9: Optimal Response of Residential House Load 242 9.1 Introduction 242 9.2 The Formulation of Appliance Commitment Problem 244 9.2.1 Thermal Dynamic Modes of EWH 245 9.2.2 The Parameter Estimation of EWH Thermal Model 246 9.2.3 The Random Hot-Water-Consumption Model 247 9.2.4 The Comfort Constraints 248 9.3 Solving the Appliance Commitment Problem 248 9.4 Case Studies 252 9.4.1 Day-Ahead Energy Price Forecast 252 9.4.2 A State Queueing Model of Water Heater 252 9.4.3 Transactive Control Strategy 253 9.4.4 Appliance Commitment 254 9.4.4.1 Day-Ahead Schedule 255 9.4.4.2 Real-Time Adjustment 257 9.4.4.3 The Selection of Comfort Settings 258 9.5 Future Work 259 9.6 Conclusions 260 References 260 Index 263