Grid–Integrated and Standalone Photovoltaic Distributed Generation Systems – Analysis, Design, and Control

DR. BO ZHAO is a Senior Research Engineer at State Grid Zhejiang Electric Power Research Institute, and the director of Zhejiang Province Key Laboratory of Distribution Generation and Microgrid Technologies in China. DR. CAISHENG WANG is an Associate Professor with the Electrical and Computer Engineering Department, Wayne State University, Detroit, USA. DR. XUESONG ZHANG is a Senior Research Engineer at State Grid Zhejiang Electric Power Research Institute, Hangzhou, China.

• Preface xiii1 Overview 11.1 Current Status and Future Development Trends of Photovoltaic Generation around theWorld 11.1.1 USA 31.1.2 Japan 51.1.3 Germany 51.1.4 China 61.2 Current Research Status of Grid-Connected Photovoltaic Generation 81.2.1 Characteristics of Grid-Connected Photovoltaic Generation 81.2.2 Impact of High-Penetration Photovoltaic Generations on Distribution Networks 91.2.3 Research Needs on Massive Distributed Grid-Connected Photovoltaic Generation 111.3 Summary 13References 142 Techniques of Distributed Photovoltaic Generation 172.1 Introduction to Distributed Photovoltaic Generation 172.1.1 Distributed Generation: Definition and Advantages 172.1.2 Principle and Structure of Distributed Photovoltaic Generation 182.2 Photovoltaic Cells 202.2.1 Classification of the Photovoltaic Cells 202.2.1.1 Classification Based on Cell Structure 202.2.1.2 Material-based PV Cell Classification 212.2.2 Development History of Solar Cells 212.2.3 Model of a Silicon Solar Cell 222.3 Inverter 262.3.1 Topology of Connection between Inverter and Photovoltaic Module 262.3.2 The Classification and Characteristics of the Inverter 282.3.3 Requirements of a Grid-Connected Photovoltaic Inverter 292.4 Maximum Power Point Tracking Control 322.4.1 Hill Climbing/Perturb and Observe 332.4.2 Incremental Conductance 342.4.3 Open-Circuit Voltage Method 362.4.4 Short-Circuit Current Method 362.4.5 Ripple Correlation Control 362.4.6 Load Current or Load Voltage MaximizationMethod 372.4.7 dP/dV or dP/dI Close-Loop Control 382.4.8 Maximum Power Point Tracking Efficiency 382.5 Summary 39References 403 Load Characteristics in Distribution Networks with Distributed Photovoltaic Generation 433.1 Introduction 433.2 Load Characteristics of a Distribution Network 433.2.1 Load Types and Indices 433.2.2 Time-Sequence Characteristics of Typical Loads 453.2.3 Case Study 463.3 The Output Characteristics of Photovoltaic Generation 483.3.1 Regulations on Grid-Connected Photovoltaic Generation 483.3.2 Time-Sequence Characteristics of Photovoltaic Generation 493.3.3 Case Study 513.4 Characteristics of the Net Load in a Distribution Network with Distributed Photovoltaic Generation 533.4.1 Influence of Distributed Photovoltaic Generation on System Load Level 543.4.2 Influences of Distributed Photovoltaic Generation on Load Fluctuation 563.5 Power and Energy Analysis of Distributed Photovoltaic Generation 573.5.1 Effective Power and Equivalent Electricity Generation of Distributed Photovoltaic Generation 573.5.2 CalculationMethods of the Correction Coefficients 583.6 Summary 61References 624 Penetration Analysis of Large-Scale Distributed Grid-Connected Photovoltaics 654.1 Introduction 654.2 Economic Analysis of Distributed Photovoltaic Systems 664.2.1 Cost/Benefit Analysis of Distributed Grid-Connected Photovoltaic Systems 664.2.1.1 Cost Composition 664.2.1.2 Income Composition 674.2.2 Grid Parity 684.3 Large-Scale Photovoltaic Penetration Analysis 704.3.1 Further Explanation of Some Concepts 704.3.2 Concepts and Assumptions 714.3.2.1 Basic Concepts 714.3.2.2 Basic Assumptions 734.3.3 Power Penetration Analysis 734.3.4 Photovoltaics Penetration with Different Types of Load 794.4 Maximum Allowable Capacity of Distributed Photovoltaics in Distribution Network 824.4.1 Static Characteristic Constraint Method 824.4.1.1 Voltage Constraint 834.4.1.2 Protection 834.4.1.3 Harmonic Limit 854.4.2 Constrained OptimizationMethod 864.4.3 Digital SimulationMethod 874.4.3.1 Maximum Allowable Photovoltaic Capacity in Static Simulation 874.4.3.2 Maximum Allowable Photovoltaic Capacity in Dynamic Simulations 874.5 Maximum Allowable Capacity of Distributed Photovoltaics Based on Random Scenario Method 884.5.1 Algorithm Introduction 884.5.2 Case Study 894.6 Photovoltaic Penetration Improvement 934.6.1 Full Utilization of the Reactive Power Regulation Capability of a Distributed Photovoltaic System 934.6.2 Distribution Network Upgrade 934.6.3 Demand-Side Response 934.6.4 Energy Storage Technologies 944.7 Summary 94References 945 Power Flow Analysis for Distribution Networks with High Penetration of Photovoltaics 975.1 Introduction 975.2 Power Flow Calculation for Distribution Networks with Distributed Photovoltaics 975.2.1 Comparison between Power Flow Calculation Methods for Distribution Networks 975.2.2 Power Flow CalculationModel for a Distributed Photovoltaics 995.2.3 Power Flow CalculationMethod for Distribution Network with Distributed Photovoltaics 1005.3 Voltage Impact Analysis of Distributed Photovoltaics on Distribution Networks 1015.3.1 MathematicalModel 1015.3.2 Simulation Studies 1035.4 Loss Analysis in Distribution Network with Distributed Photovoltaics 1085.4.1 MathematicalModel 1085.4.2 Simulation Results 1105.5 Real Case Studies 1125.5.1 Patterns for Distributed Photovoltaics Interconnection 1125.5.2 Analysis on a Feeder 1145.5.3 Analysis on SA Substation 1185.6 Summary 123References 1236 Voltage Control for Distribution Network with High Penetration of Photovoltaics 1256.1 Introduction 1256.2 Voltage Impact Analysis in the Distribution Network with Distributed Photovoltaics 1266.3 Voltage Control Measures 1306.3.1 Automatic Voltage Control System 1306.3.2 Feeder-Level Voltage Regulation 1306.3.3 Photovoltaic Inverter 1316.4 Photovoltaic Inverter Control Strategies 1326.4.1 General Control Principle 1326.4.2 Constant Power Factor Control Strategy 1326.4.3 Variable Power Factor Control Strategy 1336.4.4 Voltage Adaptive Control Strategy 1346.4.4.1 Q/V Droop Control 1346.4.4.2 P/V Droop control 1366.4.4.3 Inverter Parameter Optimization 1366.5 Modeling and Simulation 1376.5.1 Approaches 1376.5.2 Introduction to OpenDSS 1386.5.3 SimulationModels 1386.5.3.1 Automatic Voltage Control System 1396.5.3.2 Photovoltaic SystemModel 1426.6 Simulation Analysis 1446.6.1 Basic Data Preparation for Simulation 1446.6.2 Analysis of Power Flow and Voltage in Extreme Scenarios with Automatic Voltage Control 1476.6.2.1 Working Day (July 16, 2014) Scenario 1476.6.2.2 Holiday (May 1, 2014) Scenario 1496.6.3 Participation of Photovoltaic Inverter in Voltage Regulation 1516.6.3.1 Working Day (July 16, 2014) Scenario 1516.6.3.2 Holiday (May 1, 2014) Scenario 1566.7 Summary 163References 1637 Short-Circuit Current Analysis of Grid-Connected Distributed Photovoltaic Generation 1657.1 Introduction 1657.2 Short-Circuit Characteristic Analysis of Distributed Photovoltaic Generation 1657.2.1 Short-Circuit Characteristic Analysis of Symmetric Voltage Sag of Power Grid 1667.2.2 Short-Circuit Characteristic Analysis of Asymmetrical Voltage Sag of Power Grid 1677.3 Low-Voltage Ride-Through Techniques of Photovoltaic Generation 1697.3.1 Review of Low-Voltage Ride-Through Standards 1707.3.2 Low-Voltage Ride-Through Control Strategy for Photovoltaic Generation 1717.4 Simulation Studies 1747.4.1 Fault Simulations of Photovoltaic Generation without the Low-Voltage Ride-Through Function 1747.4.2 Fault Simulation of Photovoltaic Generation with the Low-Voltage Ride-Through Function 1767.4.2.1 Case 1: 80% Voltage Drop ofThree Phases 1767.4.2.2 Case 2: 80% Voltage Drop of Two Phases 1767.4.2.3 Case 3: 80% Voltage Drop of a Single Phase 1777.5 Calculation Method for Short-Circuit Currents in Distribution Network with Distributed Photovoltaic Generation 1797.5.1 Distribution NetworkModel 1807.5.2 Calculation Method for Short-Circuit Currents in a Traditional Distribution Network 1807.5.2.1 Operational Curve Law 1817.5.2.2 IEC Standard 1817.5.2.3 ANSI Standard 1817.5.3 Calculation Method for Short-Circuit Currents in a Distribution Network with Distributed Photovoltaic Generation 1827.5.3.1 Calculation Method for Symmetric Fault Short-Circuit Currents 1837.5.3.2 Calculation Method for Asymmetric Fault Short-Circuit Currents 1847.5.4 Fault Simulation Studies of Distribution Network with Distributed Photovoltaic Generation 1867.6 Summary 191References 1928 Power Quality in Distribution Networks with Distributed Photovoltaic Generation 1958.1 Introduction 1958.2 Power Quality Standards and Applications 1958.2.1 Power Quality Standards for Grid-Connected Photovoltaic Generation 1968.2.2 Power Quality Requirements Stipulated in Standards for Grid-Connected Photovoltaic Generation 1968.2.2.1 Voltage Deviation 1978.2.2.2 Voltage Fluctuation and Flicker 1988.2.2.3 Voltage Unbalance Factor 1998.2.2.4 DC Injection 1998.2.2.5 Current Harmonics 1998.2.2.6 Voltage Harmonics 2048.3 Evaluation and Analysis of Voltage Fluctuation and Flicker for Grid-Connected Photovoltaic Generation 2068.3.1 Evaluation Process 2078.3.1.1 First-Level Provisions 2078.3.1.2 Second-Level Provisions 2078.3.1.3 Third-Level Provisions 2088.3.2 Calculation 2088.3.2.1 The First-Level Evaluation for Photovoltaic Integration 2088.3.2.2 The Second-Level Evaluation 2088.4 Harmonic Analysis for Grid-Connected Photovoltaic Generation 2118.4.1 Fundamentals of Harmonic Analysis 2118.4.1.1 Harmonic Simulation Platform 2118.4.1.2 Photovoltaic Harmonic Model 2138.4.2 Harmonic Analysis of Photovoltaic Generation Connected to a Typical Feeder 2188.4.2.1 Harmonics Analysis of Centralized Photovoltaic Connection 2198.4.2.2 Harmonics Analysis of Photovoltaic Connection in a DistributedWay 2238.4.3 Analysis of Practical Cases 2248.5 Summary 225References 2259 Techniques for Mitigating Impacts of High-Penetration Photovoltaics 2279.1 Introduction 2279.2 Energy Storage Technology 2279.2.1 Classification of Energy Storage Technologies 2289.2.1.1 Mechanical Energy Storage 2289.2.1.2 Electromagnetic Energy Storage 2299.2.1.3 Phase-Change Energy Storage 2299.2.1.4 Chemical Energy Storage 2299.2.2 Electrochemical Energy Storage 2299.2.2.1 Lead–Acid Battery 2309.2.2.2 Lithium-Ion Battery 2319.2.2.3 Flow Cell 2329.2.3 Electrochemical Energy Storage Model 2339.2.3.1 MathematicalModel 2339.2.3.2 Life Model 2359.3 Application of Energy Storage Technology in High-Penetration Distributed Photovoltaics 2369.3.1 Siting and Sizing Methods for Energy Storage System 2369.3.1.1 Siting of Energy Storage System 2369.3.1.2 Sizing of the Energy Storage System 2379.3.2 Case Simulation 2389.4 Demand Response 2429.4.1 Introduction 2429.4.1.1 Price-Based Demand Response 2429.4.1.2 Incentive-Based Demand Response 2439.4.2 Load Characteristics of Demand Response 2459.5 Application of Demand Response in Distribution Networks with High Penetration of Distributed Photovoltaics 2479.5.1 Incentive-Based Demand Response OptimizationModel 2479.5.1.1 Incentive-Based Demand Response Model 2479.5.1.2 Constraints 2499.5.2 Incentive-Based Demand Response Algorithm 2499.5.3 Case Simulation 2519.6 Cluster Partition Control 2529.7 Application of Cluster Partition Control in Distributed Grid with High-Penetration Distributed Photovoltaics 2569.7.1 Community-Detection-Based Optimal Network Partition 2569.7.2 Sub-community Reactive/Active Power-Voltage Control Scheme 2599.7.3 Case Study 2619.8 Summary 270References 27110 Design and Implementation of Stand-aloneMultisource Microgrids with High-Penetration Photovoltaic Generation 27310.1 Introduction 27310.2 System Configurations of Microgrids with Multiple Renewable Sources 27410.2.1 Integration Schemes 27410.2.2 Unit Sizing and Technology Selection 27710.3 Controls and Energy Management 27810.3.1 Centralized Control Paradigm 27810.3.2 Distributed Control Paradigm 27910.3.3 Hybrid Hierarchical Control Paradigm 28010.4 Implementation of Stand-alone Microgrids 28110.4.1 Dongfushan Microgrid: Joint Optimization of Operation and Component Sizing 28210.4.1.1 System Configuration 28210.4.1.2 Operating Strategy 28310.4.1.3 OptimizationModel 28710.4.1.4 System Sizing Optimization 29110.4.1.5 Optimal Configuration and Operation Practice 29710.4.2 Plateau Microgrid: A Multiagent-System-Based Energy Management System 29910.4.2.1 System Configuration 29910.4.2.2 Multiagent-System-Based Energy ManagementMethod 30110.4.2.3 Validation of the Microgrid Energy Management System 30710.5 Summary 309References 310Index 315