Electricity Distribution (eBook)

Panagiotis Karampelas holds a Ph.D. in Electronic Engineering from University of Kent at Canterbury, UK and an MSc in “High Performance Algorithms” from the Department of Informatics, University of Athens, Greece. He has worked a lot of years as a researcher and as a faculty member in various research and educational institutions. His areas of interest include Information Visualization, Data Mining, Social Network Analysis, Artificial Neural Networks, Power Transmission and Distribution Systems. He has published a number of articles in his major areas of interests in international journals, conferences and books. Currently, he is a Lecturer at the Hellenic Air Force Academy, Greece. Lambros Ekonomou received a Bachelor of Engineering (Hons) in Electrical Engineering and Electronics in 1997 and a Master of Science in Advanced Control in 1998 from University of Manchester Institute of Science and Technology (U.M.I.S.T.) in United Kingdom. In 2006 he graduated with a Ph.D. in High Voltage Engineering from the National Technical University of Athens (N.T.U.A.) in Greece and with a BA in Economics from University of Piraeus in Greece. His research interests include power systems, transmission and distribution lines, distributed generation, lightning and artificial neural networks. He has worked as a faculty member in various institutions such as City University London, ASPETE - School of Pedagogical and Technological Education, Hellenic Military Academy, Hellenic American University and Hellenic Naval Academy. He has also worked as senior electrical engineer in various companies including Hellenic Public Power Corporation S.A., Athens-Piraeus Electric Railways S.A. and Hellenic Aerospace Industry S.A.

Preface 6
Contents 8
1 A Methodology for Web-Based Power Systems Simulation and Analysis Using PHP Programming 10
Abstract 10
1 Introduction 11
2 Web-Based Power Systems Simulation Software 14
2.1 Commercial and Open Source Web-Based Power Systems Simulation Software 14
2.1.1 InterPSS 14
2.1.2 NEPLAN 360 15
2.1.3 MATLAB Based Systems: SimPowerSystems and MATPOWER 15
2.2 Web-Based Power Systems Simulation in Previous Research Work 16
2.3 Advantages and Disadvantages of Using a PHP Simulation Engine for Power Systems Simulation 16
3 Methodology 19
3.1 Extending the Functionality of PHP to Handle Power Systems Simulation Concepts 20
3.1.1 Matrix Operations 20
3.1.2 Complex Number and Vector Operations 21
3.2 PHP Simulation Engine Classes 21
3.2.1 Network Definition in PHP Classes 23
3.2.2 Newton-Raphson Power Flow Solution in PHP Classes 24
3.2.3 Newton-Raphson Power Flow PHP Application Flowchart 26
4 Results and Discussion 26
4.1 Networks Tested and Parameters Observed 27
4.2 Discussion 27
5 Conclusion 31
References 32
2 Integration of Dispersed Power Generation 35
Abstract 35
1 Introduction 36
2 Evaluation of the Probability Distributions of Reliability Indices in Electricity Distribution Systems Using Monte Carlo Simulation 37
2.1 Reliability Indices 39
2.1.1 Definition of the Reliability Indices 39
2.1.2 Expected Value of the Interruption Duration at Load Point K 40
2.2 Distribution System Structure and Analysis 41
2.2.1 Network Structure and Definitions 41
2.2.2 Extracting L and ? Matrices Out of the Test-Network 43
2.3 Application of the Monte Carlo Method 44
2.3.1 General Hypotheses 44
2.3.2 The Sequential Monte Carlo Method 45
2.4 Mean Value Calculated with Analytical Methods 48
2.4.1 Number of Interruptions N 48
2.4.2 Power not Supplied PNS 49
2.4.3 Interruption Time d 50
2.4.4 Interruption Time d 51
3 Role of Statistical Profiling for Energy Markets. Load Profiles Definition for Electricity Market 51
3.1 Operational and Functional Requirements for Accurate Load Profiling—Analytical Assessment 51
3.1.1 Monthly Energy Aggregation 55
3.1.2 Evaluation of Energy Weights 56
3.1.3 Monthly Energy Calculation 56
3.1.4 Monthly Calculation of Energy Weights 57
3.1.5 Daily/Hourly Energy Calculation 57
3.2 System Application 58
3.2.1 Daily/Hourly Energy Calculation 58
3.2.2 Small Businesses Without Cooling 59
3.2.3 Small Businesses with Cooling 59
4 Operation of Distribution Systems with Dispersed Generation 61
4.1 Operational Aspects of Voltage Control 61
5 Conclusions 64
References 66
3 Islanding Detection Methods for Distributed PV Systems Overview and Experimental Study 70
Abstract 70
1 Introduction 71
2 Passive Islanding Detection Techniques 72
2.1 The U/O-V& F Monitoring Technique
2.2 ?he Voltage Phase Jump (VPJ) Monitoring Technique 73
2.3 ?he Voltage Harmonics Detection (VHD) Monitoring Technique 74
3 Active Islanding Detection Techniques 75
3.1 Impedance Measurement Monitoring Technique 75
3.2 The Impedance Detection at a Specific Frequency (IDSF) Monitoring Technique 76
3.3 The Slip-Mode Frequency Shift (SMFS) Monitoring Technique 76
3.4 The Active Frequency Drift Monitoring Technique 77
3.5 The Sandia Frequency Shift (SFS) Monitoring Technique 77
3.6 ?he Sandia Voltage Shift (SVS) Monitoring Technique 78
4 Hybrid Islanding Detection Techniques 79
5 Islanding Detection Techniques Test Procedure According to IEC 62116 79
6 Experimental Evaluation of Islanding Detection Techniques 81
7 Conclusions 85
Acknowledgment 85
References 85
4 The Use of PLC Technology for Smart Grid Applications Over the MV Grid: The DG Paradigm 87
Abstract 87
1 Introduction 87
2 Smart Grid and Distributed Generation 88
2.1 The Smart Grid 88
2.1.1 The Communication Infrastructure of the Smart Grid 90
2.1.2 The Hybrid Wireless-BB PLC 91
2.2 Distributed Generation 92
2.2.1 DG Technologies 93
2.2.2 DG Advantages and Disadvantages 94
2.2.3 DG Interconnection with the Power Grid 95
3 DG Integration into the Autonomous Power Grid of an Island 96
3.1 PV Penetration in an Autonomous Island Grid. A Study Case 96
3.1.1 Autonomous Grids 97
3.1.2 Interconnection Issues When PV Systems Are Integrated into the MV Grids of Greek Islands 97
3.1.3 Voltage Fluctuations 99
3.1.4 Power Factor at the MV Bus 99
3.2 Autonomous Power Grids in Islands 100
4 Mathematical Formulation of the Study Case 101
4.1 AS Generation Plant Bus 101
4.2 PV Units 102
4.3 Energy and Power Calculations 105
5 Numerical Simulations 108
5.1 MV Line Without Any PV Units Connected 108
5.2 MV Line Enhanced with Eight PV Units Without Control 112
5.3 Monitored and Managed MV Line with Eight PV Units Connected 116
6 Design Guidelines for the PLC Based SG Scheme to Monitor and Control the Distributed PV Units 120
7 Conclusions 122
References 123
5 The Correlation Between Renewable Generation and Electricity Demand: A Case Study of Portugal 124
Abstract 124
1 Introduction 125
2 Related Work 126
3 Electric Sector in Portugal 128
3.1 Evolution and Legal Framework 128
3.2 Current Situation 128
3.2.1 Generation 128
3.2.2 Transmission 129
3.2.3 Distribution 129
3.2.4 Supply 130
3.2.5 Regulation 130
3.3 National Energy Strategy 2020 130
3.4 Integration of Renewables into the Electric System 134
3.4.1 Transmission Requirements 135
3.4.2 Distributed Generation 135
3.4.3 Variability 136
3.4.4 Intermittency 137
3.4.5 ‘Smart Grid’ Technologies 138
4 Case Study 139
4.1 Objectives 139
4.2 Methodology 139
4.3 Availability of Resources in Portugal 142
4.3.1 Solar 142
4.3.2 Wind 143
4.3.3 Hydro 146
4.4 Variation of Electricity Demand in Portugal 148
4.5 Findings and Discussion 149
4.6 Limitations of the Study 153
5 Conclusions 154
References 155
6 A Robust Iterative Learning Control Algorithm for Uncertain Power Systems 157
Abstract 157
1 Introduction and Problem Statement 157
2 The ILC Problem 159
3 Positive Invariance of Polyhedral Sets 162
4 A Design Algorithm for Robust Convergence 166
5 Constrained Iterative Learning Control 168
5.1 Mean Value Constraints 169
6 Example 171
7 Conclusion 173
References 174
7 Damping of Power System Oscillations with Optimal Regulator 176
Abstract 176
1 Introduction 177
2 Optimal Control Theory 178
2.1 Optimal State Feedback 178
2.2 Optimal Output Feedback 182
3 Optimal Regulators Design 183
3.1 Optimal State Feedback Design 183
3.1.1 Weighting Matrices Specification 184
3.1.2 Algorithm to Specify the Weighting Matrices 186
3.2 Optimal Output Feedback Design 186
3.2.1 Algorithm to Calculate the Optimal Output Feedback Gains 189
4 Description of the Test Power Sensitivity and PSS Models 190
5 Illustration Results 192
5.1 State Feedback Optimal Regulator 193
5.2 Output Feedback Regulator 194
5.3 Controllers Time Response Analysis 194
6 Conclusion 200
Appendix 200
References 200
8 Design of Three-Phase LCL-Filter for Grid-Connected PWM Voltage Source Inverter Using Bacteria Foraging Optimization 202
Abstract 202
1 Introduction 202
2 System Modelling and Description 204
2.1 Grid-Current Feedback 206
2.2 Converter-Current Feedback 206
3 Optimum Damping Control of LCL-Filter 208
4 Design Tools 210
4.1 Bacteria Foraging Optimization (Bfo) 210
4.1.1 Chemotaxis 210
4.1.2 Reproduction 211
4.1.3 Elimination and Dispersal 211
4.2 LCL-Filter Design Algorithm 211
5 Results 213
5.1 Simulation Results 213
5.2 Experimental Results 214
6 Conclusions 218
Appendix 1 218
Appendix 2 220
References 220
9 Real Time Monitoring of Incipient Faults in Power Transformer 223
Abstract 223
1 Introduction 223
2 Module of Data Transfer 226
2.1 Measurement Unit 226
2.2 “High Level”—Registration Unit 227
2.3 Decoder Program 228
3 Module of Comparison 229
4 Module of Calculation 231
5 Module of Visualization 232
6 Module of Classification 234
7 Module of Decision 236
References 242
10 Advanced Short-Circuit Analysis for the Assessment of Voltage Sag Characteristics 243
Abstract 243
1 Introduction 243
2 Advanced Short-Circuit Analysis 244
2.1 Fault Position f as a New Bus 246
2.2 Pre-fault Voltage {/varvec{/tilde{V}_{f}^{pref} (/ell )}} as a Function of Fault Distance 246
2.3 Non-diagonal Element {/varvec{Z_{kf} (/ell )}} Versus Fault Distance 247
2.4 Diagonal Element {/varvec{Z_{ff} (/ell )}} Versus Fault Distance 248
3 Analytical Expressions Per Fault Type Versus Fault Distance 249
3.1 Three-Phase Faults 249
3.2 One-Phase-to-Ground Faults 250
3.3 Two-Phase Faults 251
3.4 Two-Phase-to-Ground Faults 252
4 Effects of Phase-Shifting Transformers or Devices 255
4.1 Incorporation of Phase Shift on Analytical Expressions 256
4.2 Transformer’s Phase-Shift and Sag Magnitude 256
5 Further Processing of Analytical Expressions 257
6 Study Case 260
7 Results and Discussion 262
7.1 No Phase-Shifting Devices 263
7.2 Effect of Transformer’s Phase Shift 264
8 Conclusions 266
References 267
11 A Genetic Proportional Integral Derivative Controlled Hydrothermal Automatic Generation Control with Superconducting Magnetic Energy Storage 268
Abstract 268
1 Introduction 268
2 Hydrothermal Power Systems Model 270
3 Superconducting Magnetic Energy Storage 271
4 Overview of Genetic Algorithm (GA) 274
5 Optimization of PID Gain Settings 279
6 Dynamic Responses 280
7 Conclusion 283
Appendix 283
References 284
12 Linguistic Representation of Power System Signals 286
Abstract 286
1 Introduction 286
2 Theoretical Background 288
3 The Syntactic Approach in Power Systems Signals 289
3.1 Primitive Pattern Selection 289
3.2 Linguistic Representation 291
3.3 Pattern Grammar AGPS 291
4 An Illustrative Example 292
5 Conclusions and Future Work 294
References 295
13 Levenberg-Marquardt Algorithm Based ANN for Nodal Price Prediction in Restructured Power System 297
Abstract 297
1 Introduction 297
2 Optimal Power Flow Based Nodal Price 299
2.1 Formulation of Nodal Price 299
2.2 Artificial Neural Network for Nodal Price Prediction 301
2.3 Vector Quantization Clustering Technique 304
3 Development of LMANN for Nodal Price Prediction 305
3.1 Methodology Used for Training an ANN 305
3.2 Feature Selection 306
4 Results and Discussion 307
4.1 6-Bus Power System 307
4.2 RTS 24-Bus System 311
5 Conclusion 317
References 317