Cover image for Electric systems, dynamics, and stability with artificial intelligence applications
Title:
Electric systems, dynamics, and stability with artificial intelligence applications
Personal Author:
Series:
Power engineering
Publication Information:
New York, NY : Marcel Dekker, 2000
ISBN:
9780824702335
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30000010080075 TK1010 M65 2000 Open Access Book Book
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Summary

Summary

This work seeks to provide a solid foundation to the principles and practices of dynamics and stability assessment of large-scale power systems, focusing on the use of interconnected systems - and aiming to meet the requirements of today's competitive and deregulated environments. It contains easy-to-follow examples of fundamental concepts and algorithmic procedures.


Author Notes

Mohamed E. El-Hawary is a Professor of Electrical and Computer Engineering and Associate Dean of Engineering at Dalhousie University, Halifax, Nova Scotia, Canada.


Table of Contents

H. Lee Willis
Series Introductionp. v
Prefacep. vii
1 Introductionp. 1
1.1 Historical Backgroundp. 1
1.2 Structure at a Generic Electric Power Systemp. 3
1.3 Power System Security Assessmentp. 7
2 Static Electric Network Modelsp. 10
Introductionp. 10
2.1 Complex Power Conceptsp. 11
2.2 Three-Phase Systemsp. 14
2.3 Synchronous Machine Modelingp. 21
2.4 Reactive Capability Limitsp. 31
2.5 Static Load Modelsp. 32
Conclusionsp. 35
3 Dynamic Electric Network Modelsp. 36
Introductionp. 36
3.1 Excitation System Modelp. 36
3.2 Prime Mover and Governing System Modelsp. 40
3.3 Modeling of Loadsp. 43
Conclusionsp. 44
4 Philosophy of Security Assessmentp. 45
Introductionp. 45
4.1 The Swing Equationp. 46
4.2 Some Alternative Formsp. 47
4.3 Transient and Subtransient Reactancesp. 50
4.4 Synchronous Machine Model in Stability Analysisp. 55
4.5 Subtransient Equationsp. 59
4.6 Machine Modelsp. 59
4.7 Groups of Machines and the Infinite Busp. 63
4.8 Stability Assessmentp. 63
4.9 Concepts in Transient Stabilityp. 68
4.10 A Method for Stability Assessmentp. 71
4.11 Mathematical Models and Solution Methods in Transient Stability Assessment for General Networksp. 82
4.12 Integration Techniquesp. 89
4.13 The Transient Stability Algorithmp. 98
Conclusionsp. 108
5 Assessing Angle Stability via Transient Energy Functionp. 109
Introductionp. 109
5.1 Stability Conceptsp. 110
5.2 System Model Descriptionp. 117
5.3 Stability of a Single-Machine Systemp. 118
5.4 Stability Assessment for n-Generator System by the TEF Methodp. 121
5.5 Application to a Practical Power Systemp. 126
5.6 Boundary of the Region of Stabilityp. 127
Conclusionp. 131
6 Voltage Stability Assessmentp. 132
Introductionp. 132
6.1 Working Definition of Voltage Collapse Study Termsp. 134
6.2 Typical Scenario of Voltage Collapsep. 135
6.3 Time-Frame Voltage Stabilityp. 136
6.4 Modeling for Voltage Stability Studiesp. 136
6.5 Voltage Collapse Prediction Methodsp. 138
6.6 Classification of Voltage Stability Problemsp. 138
6.7 Voltage Stability Assessment Techniquesp. 140
6.8 Analysis Techniques for Steady-State Voltage Stability Studiesp. 145
6.9 Parameterizationp. 151
6.10 The Technique of Modal Analysisp. 156
6.11 Analysis Techniques for Dynamic Voltage Stability Studiesp. 157
Conclusionp. 169
Modeal Analysis: Worked Examplep. 170
7 Technology of Intelligent Systemsp. 175
Introductionp. 175
7.1 Fuzzy Logic and Decision Treesp. 177
7.2 Artificial Neural Networksp. 177
7.3 Robust Artificial Neural Networkp. 184
7.4 Expert Systemsp. 191
7.5 Fuzzy Sets and Systemsp. 206
7.6 Expert Reasoning and Approximate Reasoningp. 214
Conclusionp. 220
8 Application of Artificial Intelligence to Angle Stability Studiesp. 221
Introductionp. 221
8.1 ANN Application in Transient Stability Assessmentp. 222
8.2 A Knowledge-Based System for Direct Stability Analysisp. 238
Conclusionsp. 257
9 Application of Artificial Intelligence to Voltage Stability Assessment and Enhancement to Electrical Power Systemsp. 259
Introductionp. 259
9.1 ANN-Based Voltage Stability Assessmentp. 260
9.2 ANN-Based Voltage Stability Enhancementp. 265
9.3 A Knowledge-Based Support System for Voltage Collapse Detection and Preventionp. 272
9.4 Implementation for KBVCDPp. 278
9.5 Utility Environment Applicationp. 287
Conclusionp. 287
10 Epilogue and Conclusionsp. 289
Glossaryp. 298
Appendix Chapter Problemsp. 311
Bibliographyp. 332
Indexp. 351