Advances in Solar Photovoltaic Power Plants (eBook)

Contents 6
About the Editors 8
Acronyms 8
Symbols 8
List of Figures 8
List of Tables 8
1 Introduction 39
Abstract 39
1 Preface 40
2 Major Objectives of the Book 45
3 Organization of the Book 45
4 Summary 48
References 48
2 Photovoltaic Inverter Topologies for Grid Integration Applications 50
Abstract 50
1 Introduction 50
2 Overview of PV Configuration for Grid Integration 52
2.1 Centralized Configuration 52
2.2 Module Configuration 54
2.3 String Configuration 56
2.4 Multi-string Configuration 58
3 Common-Mode Behavior 60
4 Leakage Current Reduction Methods 63
4.1 Galvanic Isolation 63
4.2 CMV Clamping 64
5 Transformerless PV Inverter Topologies 66
5.1 Full-Bridge Topology 66
5.2 H5 Topology 67
5.3 HERIC Topology 69
5.4 H6 Topology 71
5.5 oH5 Topology 72
5.6 HBZVR-D Topology 75
6 Loss Analysis 75
7 Summary 77
References 78
3 Advanced Control Techniques for PV Maximum Power Point Tracking 80
Abstract 80
1 Introduction 81
2 The Physical Basis and Mathematical Model of PV 82
2.1 The Mathematical Model 82
2.2 The Output Characteristic of the PV Cell 83
3 The Basic Theory of MPPT 85
4 The Basic Topologies of PV System for MPPT 86
4.1 The Two-Stage Grid-Connected Structure 86
4.1.1 The MPPT Control Based on the Inverter 86
4.1.2 The MPPT Control Based on DC/DC Converter 87
4.2 Single-Stage Grid-Connected Structure 88
4.2.1 The Three-Loop Control Structure 89
4.2.2 Dual-Loop Control Structure 89
5 The Advanced MPPT Method 90
5.1 The Fuzzy Algorithm 90
5.1.1 Fuzzification 91
5.1.2 Fuzzy Reasoning Arithmetic 92
5.1.3 Defuzzification 92
5.2 MPPT Control Based on Neural Networks 93
5.2.1 Preliminaries 93
5.2.2 Neural Network-Based Control 94
5.3 The Variable Step-Size MPPT Method 96
5.3.1 The Improved Variable Step-Size Algorithm 97
5.3.2 One Novel Variable Step-Size Algorithm 99
5.4 The Iterative Algorithm 102
5.4.1 Novel Linear Iteration Method 102
5.5 The Probability Algorithm 108
5.5.1 The Constant Voltage Tracking 108
5.5.2 The Probability Algorithm 110
6 Conclusion 113
References 113
4 Maximum Power Point Tracking Methods for PV Systems 116
Abstract 116
1 Introduction 116
2 Criteria for Assessing MPPT Methods 118
3 Conventional MPPT Methods 118
3.1 Maximum Power Point Estimation 119
3.2 Hill Climbing Methods 120
3.3 Artificial Intelligence Methods 125
3.4 Other Methods 126
3.4.1 Beta Method 126
3.4.2 Parabolic Curve Prediction 127
3.4.3 Ripple Correlation Control 128
3.4.4 Extremum Seeking Control 128
3.4.5 Bisection Search Theorem 128
3.4.6 Sliding Mode Control 129
3.4.7 Optimisation of Output Parameters 129
4 Methods Designed for MPPT Under Non-uniform Environmental Conditions 130
4.1 Modification of Conventional Techniques for MPPT Under Non-uniform Environmental Conditions 130
4.1.1 Periodic Reset and Periodic Curve Scanning 131
4.1.2 Widening Search Range 131
4.1.3 Two-Stage Method 132
4.2 Techniques Based on Observations of the I–V and P–V Characteristics for MPPT Under Non-uniform Environmental Conditions 132
4.3 Techniques Designed Specifically MPPT Under Non-uniform Environmental Conditions 133
4.3.1 Line Search 133
4.3.2 Particle Swarm Optimisation 134
4.3.3 Simulated Annealing 135
4.3.4 Chaos Search 136
5 Conclusion 136
References 137
5 Photovoltaic Multiple Peaks Power Tracking Using Particle Swarm Optimization with Artificial Neural Network Algorithm 143
Abstract 143
1 Introduction 144
2 PV Arrays Under Partial Shaded Conditions 145
3 Particle Swarm Optimization (PSO) Algorithm 147
4 Artificial Neural Network (ANN) Algorithm 148
5 The Proposed Multiple Peaks MPPT 149
6 Simulation Setup 152
7 Hardware Experimental Setup 157
8 Results and Discussion 162
8.1 Simulation Results 162
8.2 Experimental Results 168
9 Conclusion 171
References 171
6 Empirical-Based Approach for Prediction of Global Irradiance and Energy for Solar Photovoltaic Systems 175
Abstract 175
1 Introduction 176
1.1 Single Parametric Models for Prediction of Solar Irradiance 177
1.1.1 Single Parametric Sunshine-Based Model 178
1.1.2 Single Parametric-Based Temperature Model 179
1.2 Multi-Parametric or Hybrid Models for Prediction of & !blank
1.3 Multi-parametric Model for Prediction of Energy Generation 181
2 Formulation of Multi-parametric Global Irradiance Prediction Model 181
2.1 Input Factors Considered Affecting Global Solar Irradiance 183
2.1.1 Relative Sunshine Hour 183
2.1.2 Temperature Ratio 184
2.1.3 Air Mass at Solar Noon 185
3 Modified Multi-parametric Empirical Model 187
3.1 Case Studies for the Prediction of Global Horizontal Irradiance 187
3.2 Performance Study of Irradiance Prediction Models 189
4 Energy Prediction Model Emphasized Through Performance and Exergy Analysis 193
4.1 Performance Analysis of Solar PV Distribution System (Grid Connected PV System) 194
4.2 Exergy Analysis of Solar PV System 196
4.2.1 Assessment of Thermal Exergy Loss 197
4.2.2 Formulation of Empirical Model for Energy Prediction 199
5 Summary 201
References 202
7 A Study of Islanding Mode Control in Grid-Connected Photovoltaic Systems 205
Abstract 205
1 Introduction 206
2 The Principle of Islanding in Distribution Generation Systems 208
2.1 Types of Islanding 209
2.2 The Needs of Islanding Prevention 210
3 Anti-islanding Detection Methods 210
3.1 Local Anti-islanding Detection Method 212
3.1.1 Passive Method 212
Voltage Protection and Frequency Protection 214
Voltage Phase Jump Detection 216
Detection of Voltage and Current Harmonic 217
Other Passive Islanding Detection Methods 218
3.1.2 Active Method 219
Impedance Measurement 220
Frequency Bias 222
Sandia Voltage Shift 224
Sandia Frequency Shift 224
Other Active Islanding Detection Methods 225
3.1.3 Hybrid Anti-islanding Method 225
3.2 Remote Anti-islanding Detection Method 226
3.2.1 Utility Method 227
Impedance Insertion 227
3.2.2 Communication Anti-islanding Method 228
Transfer Trip Scheme 229
Power Line Carrier Communication (PLCC) 229
Other Communication Islanding Detection Methods 231
4 Comparisons and Discussions 231
5 Simulation of Islanding Mode Control 234
5.1 Simulation of the Voltage and Frequency Protection 234
5.2 Simulation of the Active Frequency Drift 238
6 Conclusion 245
References 246
8 Stability Assessment of Power Systems Integrated with Large-Scale Solar PV Units 251
Abstract 251
1 Introduction 251
2 System Description 253
2.1 Synchronous Generator 253
2.2 Solar PV Generator 254
3 Static Analysis 256
3.1 Voltage Profile of the System 256
3.2 Power Loss of the System 257
3.3 Static Voltage Stability of the System 258
4 Dynamic Analysis 259
4.1 Case 1: Sudden Disconnection of Line 259
4.2 Case 2: Short Circuit Fault 263
5 Summary 264
Acknowledgement 265
References 265
9 Energy Storage Technologies for Solar Photovoltaic Systems 267
Abstract 267
1 Introduction 267
2 Electricity and Its Storage 269
3 Renewable Energy from PV Generation and Storage 270
4 Energy Storage Technologies 272
5 Role of Energy Storage Technology 273
6 Different Energy Storage Technologies 273
6.1 Mechanical Energy Storage 274
6.1.1 Pumped Hydroelectric Storage 274
6.1.2 Compressed Air Energy Storage 275
6.2 Electrical Energy Storage 276
6.2.1 Superconducting Magnetic Energy Storage 276
6.2.2 Electrochemical Capacitors (Supercapacitors) 277
Electric Double Layer Capacitors 277
Pseudocapacitors 278
6.3 Chemical Energy Storage (Batteries) 279
6.3.1 Lead–Acid Battery 280
6.3.2 Nickel–Cadmium Battery 281
6.3.3 Sodium–Sulphur Battery 281
6.3.4 Sodium Nickel Chloride Battery 282
6.3.5 Lithium-Ion Battery 283
7 Conclusions and Future Perspective 285
References 285
10 Superconducting Magnetic Energy Storage Modeling and Application Prospect 288
Abstract 288
1 Introduction to Energy Storage 289
2 SMES Modeling and Verification 292
2.1 Energy Exchange Circuit 292
2.2 Superconducting AC Loss Calculation 295
2.3 Circuit-Field-Superconductor Coupled Model 299
2.4 Simulation Analysis 300
2.5 Experimental Verification 303
3 SMES-Based Microphotovoltaic Grid 308
3.1 Principle and System Description 308
3.2 Simulation Model and Implementation 309
3.3 SMES Coil Design 311
3.4 Performance Evaluation 313
4 Summary and Application Prospect 317
References 319
11 Recycling of Solar Cell Materials at the End of Life 321
Abstract 321
1 Introduction 321
2 Lifetime of PV Cells 323
2.1 Corrosion of PV Modules 324
2.2 Discoloration of PV Modules 324
2.3 Delamination of PV Modules 324
2.4 Breakage and Cracking of PV Modules 324
3 Composition of PV Modules 325
3.1 Crystalline Silicon PV Modules 326
3.2 Noncrystalline Silicon PV Modules 328
3.3 CdTe PV Modules 330
3.4 III–V PV Modules 332
3.5 CIGS PV Modules 333
4 Recycling Process 335
4.1 Recycling of Crystalline Silicon PV Modules 335
4.2 Recycling of Noncrystalline Silicon PV Modules 337
4.3 Recycling of CdTe PV Modules 338
4.4 Recycling of III–V PV Modules 340
4.5 Recycling of CIGS PV Modules 342
5 Benefits of PV Module Recycling 343
5.1 Valuable Materials 343
5.1.1 Gallium, 31Ga 343
5.1.2 Indium, 49In 344
5.1.3 Silver, 47Ag 345
5.1.4 Germanium, 32Ge 345
5.2 Environmental Effects 347
5.2.1 Cadmium, 48Cd 347
5.2.2 Arsenic, 33As 347
5.2.3 Lead, 82Pb 348
5.2.4 Toxic Gas 348
6 Summary 349
References 349