Energy Storage for Power System Planning and Operation

ZECHUN HU is Associate Professor at Tsinghua University, China. He has decades of experience in power system analysis, planning, and operation optimization.

• Preface xiAcknowledgements xvAbbreviation List xvii1 Introduction 11.1 Evolution of Power System and Demand of Energy Storage 11.2 Energy Storage Technologies and Their Applications in Power Systems 61.2.1 Energy Storage Technologies 61.2.2 Technical and Economic Analyses of Different Energy Storage Technologies 141.2.3 Applications of Energy Storage in Power Systems 161.3 Chapter Structure 231.4 Notes to Readers 241.4.1 Topics Not Included in This Book 241.4.2 Required Basic Knowledge 26References 262 Modeling of Energy Storage Systems for Power System Operation and Planning 352.1 Introduction 352.2 Pumped Hydroelectric Storage System 362.2.1 Operation of a Pumped Hydroelectric Storage System 362.2.2 Steady-State Model of a Pumped Hydroelectric Storage System 372.3 Battery Energy Storage System 392.3.1 Operation of a Battery Energy Storage System 392.3.2 Steady-State Model of a Battery Energy Storage System 412.4 Compressed Air Energy Storage System 432.4.1 Operation of a Compressed Air Energy Storage System 432.4.2 Steady-State Model of a Compressed Air Energy Storage System 462.5 Simplified Steady-State Model of a Generic Energy Storage System 482.5.1 Transformation of a Pumped Hydroelectric Storage System Model 502.5.2 Transformation of a Compressed Air Energy Storage System Model 502.5.3 Steady-State Model of a Generic Energy Storage System 512.6 Conclusion 53References 543 Day-Ahead Schedule and Bid for a Renewable Energy Generation and Energy Storage System Union 573.1 Introduction 573.2 Basic Model for Day-Ahead Schedule of a REG–ESS Union 583.3 Stochastic Optimization for Day-Ahead Coordination 593.3.1 Scenario-Based Optimization Model 593.3.2 Chance-Constrained Optimization Model 603.3.3 Case Studies on a Union of Wind Farm and Pumped Hydroelectric Storage Plant 633.4 Integrated Bidding Strategies for a REG–ESS Union 683.4.1 Day-Ahead Bidding Strategy 683.4.2 Solution Method 723.4.3 Illustrative Example 753.5 Conclusion and Discussion 77References 784 Refined Bidding and Operating Strategy for a Renewable Energy Generation and Energy Storage System Union 814.1 Introduction 814.2 Real-Time Operation with Linear Decision Rules 824.3 Optimal Offering Strategy with Linear Decision Rules 864.3.1 Objective Function 874.3.2 Constraints 894.3.3 Complete Optimization Formulation 914.3.4 Case Studies 914.4 Electricity Market Time Frame and Rules with Intraday Market 934.4.1 Day-Ahead Bidding Rules 944.4.2 Intraday Bidding Rules 954.4.3 Real-Time Operation 954.5 Rolling Optimization Framework and Mathematical Formulations Considering Intraday Markets 964.5.1 Data Flow among Different Sections 964.5.2 Initial Residue Energy of Different Optimizations 984.5.3 Optimization Model for Each Market 984.5.4 Handling Wind Power Forecast Error 1044.5.5 Case Studies 1064.6 Conclusion and Discussion 112References 1135 Unit Commitment with Energy Storage System 1175.1 Introduction 1175.2 Energy Storage System Model for SCUC 1185.3 Deterministic SCUC with Energy Storage System 1205.3.1 Objective Function 1205.3.2 Constraints 1205.3.3 Case Studies 1225.4 Stochastic and Robust SCUC with Energy Storage System and Wind Power 1305.4.1 Scenario-Based Stochastic SCUC 1305.4.2 Robust SCUC 1325.5 Conclusion and Discussion 134References 1346 Optimal Power Flow with Energy Storage System 1376.1 Introduction 1376.2 Optimal Power Flow Formulation with Energy Storage System 1386.2.1 Multi-Period OPF and Rolling Optimization 1386.2.2 Energy Storage Model for the OPF Problem 1386.2.3 OPF Formulation 1406.3 Interior Point Method to Solve the Multi-Period OPF Problem 1416.3.1 Optimal Condition for the Interior Point Method 1416.3.2 Procedure of the Primal-Dual IPM to Solve the OPF Problem 1436.3.3 Discussion on Singularities Caused by Constraints of Energy Storage System 1446.4 Semidefinite Programming for the OPF Problem 1446.4.1 Convex Relaxation of the OPF Problem 1456.4.2 Lagrange Relaxation and Dual Problem 1466.4.3 Optimal Solution of the OPF Problem 1486.5 Simulation and Comparison 1486.5.1 With a Single Energy Storage System 1486.5.2 With Multiple Energy Storage Systems 1526.6 Conclusion and Discussion 153References 1547 Power System Secondary Frequency Control with Fast Response Energy Storage System 1577.1 Introduction 1577.2 Simulation of SFC with the Participation of Energy Storage System 1587.2.1 Overview of SFC for a Single-Area System 1587.2.2 Modeling of CG and ESS as Regulation Resources 1607.2.3 Calculation of System Frequency Deviation 1607.2.4 Estimation and Allocation of Regulation Power 1627.3 Capacity Requirement for Secondary Frequency Control with Energy Storage System 1637.3.1 Procedure to Quantify Regulation Capacity Requirements 1637.3.2 Case Studies 1647.4 Control Strategies of Secondary Frequency Control with Energy Storage System 1717.4.1 CG First Power Allocation Strategy 1717.4.2 Two Other Strategies 1737.4.3 Frequency Control Performance and Cost Comparisons 1747.5 Extending to Multi-area Power System 1787.6 Conclusion and Discussion 180References 1828 Integration of Large-Scale Energy Storage System into the Transmission Network 1858.1 Introduction 1858.2 Costs and Benefits of Investing ESS in a Transmission Network 1868.3 Transmission Expansion Planning Considering Energy Storage System and Active Power Loss 1888.3.1 Objective Function and Constraints 1888.3.2 Linearization of Line Losses 1908.3.3 Sizing of Energy Storage Systems 1918.3.4 Complete Mathematical Formulation 1928.3.5 Case Studies 1948.4 Transmission Expansion Planning Considering Daily Operation of ESS 1958.4.1 Different Approaches to Consider Optimal Daily Operation 1968.4.2 Formulation of Scenario-Based Optimization 1978.5 Conclusion and Discussion 201References 2019 Optimal Planning of the Distributed Energy Storage System 2039.1 Introduction 2039.2 Benefits from Investing in DESS 2049.3 Mathematical Model for Planning Distributed Energy Storage Systems 2049.3.1 Planning Objectives 2049.3.2 Dealing with Load Variations and Uncertain DG Outputs 2059.3.3 Complete Mathematical Model with Operational and Security Constraints 2059.4 Solution Methods for the Optimal Distributed Energy Storage System Planning Problem 2099.4.1 Second-Order Cone Programming Method 2099.4.2 Two-Stage Optimization Method 2109.4.3 Solution Algorithm Based on Generalized Benders Decomposition 2119.5 Distribution Network Expansion Planning with Distributed Energy Storage System 2159.6 Conclusion and Discussion 217References 218Index 221