Preface ...................................................... xiii
Acknowledgments .............................................. xvii
1 Intelligent Power System Operation and Control: Japan
Case Study ................................................... 1
1.1 Application of Intelligent Methods to Power Systems ..... 2
1.2 Application to Power System Planning .................... 3
1.2.1 Expansion Planning of Distribution Systems ....... 3
1.2.2 Load Forecasting ................................. 4
1.2.3 Unit Commitment .................................. 5
1.2.4 Maintenance Scheduling ........................... 6
1.3 Application to Power System Control and Restoration ..... 6
1.3.1 Fault Diagnosis .................................. 6
1.3.2 Restoration ...................................... 6
1.3.3 Stabilization Control ............................ 7
1.4 Future Implementations .................................. 8
1.5 Summary ................................................. 9
References ................................................... 9
2 Automatic Generation Control (AGO: Fundamentals and
Concepts .................................................... 11
2.1 AGC in a Modern Power System ........................... 11
2.2 Power System Frequency Control ......................... 15
2.2.1 Primary Control ................................. 18
2.2.2 Supplementary Control ........................... 19
2.2.3 Emergency Control ............................... 21
2.3 Frequency Response Model and AGC Characteristics ....... 24
2.3.1 Droop Characteristic ............................ 25
2.3.2 Generation-Load Model ........................... 27
2.3.3 Area Interface .................................. 27
2.3.4 Spinning Reserve ................................ 29
2.3.5 Participation Factor ............................ 29
2.3.6 Generation Rate Constraint ...................... 29
2.3.7 Speed Governor Dead-Band ........................ 30
2.3.8 Time Delays ..................................... 30
2.4 A Three-Control Area Power System Example .............. 31
2.5 Summary ................................................ 35
References .................................................. 35
3 Intelligent AGC: Past Achievements and New Perspectives ..... 37
3.1 Fuzzy Logic AGC ........................................ 39
3.1.1 Fuzzy Logic Controller .......................... 40
3.1.2 Fuzzy-Based PI (PID) Controller ................. 43
3.2 Neuro-Fuzzy and Neural-Networks-Based AGC .............. 44
3.3 Genetic-Algorithm-Based AGC ............................ 47
3.4 Multiagent-Based AGC ................................... 50
3.5 Combined and Other Intelligent Techniques in AGC ....... 51
3.6 AGC in a Deregulated Environment ....................... 54
3.7 AGC and Renewable Energy Options ....................... 55
3.7.1 Present Status and Future Prediction ............ 56
3.7.2 New Technical Challenges ........................ 57
3.7.3 Recent Achievements ............................. 58
3.8 AGC and Microgrids ..................................... 60
3.9 Scope for Future Work .................................. 63
3.9.1 Improvement of Modeling and Analysis Tools ...... 63
3.9.2 Develop Effective Intelligent Control Schemes
for Contribution of DGs/RESs in the AGC Issue ... 64
3.9.3 Coordination between Regulation Powers
of DGs/RESs and Conventional Generators ......... 64
3.9.4 Improvement of Computing Techniques and
Measurement Technologies ........................ 64
3.9.5 Use of Advanced Communication and Information
Technology ...................................... 65
3.9.6 Update/Define New Grid Codes .................... 65
3.9.7 Revising of Existing Standards .................. 65
3.9.8 Updating Deregulation Policies .................. 66
3.10 Summary ................................................ 66
References .................................................. 67
4 AGC in Restructured Power Systems ........................... 77
4.1 Control Area in New Environment ........................ 77
4.2 AGC Configurations and Frameworks ...................... 79
4.2.1 AGC Configurations .............................. 79
4.2.2 AGC Frameworks .................................. 82
4.3 AGC Markets ............................................ 84
4.4 AGC Response and an Updated Model ...................... 86
4.4.1 AGC System and Market Operator .................. 86
4.4.2 AGC Model and Bilateral Contracts ............... 89
4.4.3 Need for Intelligent AGC Markets ................ 91
4.5 Summary ................................................ 92
References .................................................. 92
5 Neural-Network-Based AGC Design ............................. 95
5.1 An Overview ............................................ 95
5.2 ANN-Based Control Systems .............................. 97
5.2.1 Fundamental Element of ANNs ..................... 97
5.2.2 Learning and Adaptation ......................... 99
5.2.3 ANNs in Control Systems ........................ 100
5.3 Flexible Neural Network ............................... 104
5.3.1 Flexible Neurons ............................... 104
5.3.2 Learning Algorithms in an FNN .................. 105
5.4 Bilateral AGC Scheme and Modeling ..................... 107
5.4.1 Bilateral AGC Scheme ........................... 107
5.4.2 Dynamical Modeling ............................. 108
5.5 FNN-Based AGC System .................................. 110
5.6 Application Examples .................................. 113
5.6.1 Single-Control Area ............................ 115
5.6.2 Three-Control Area ............................. 117
5.7 Summary ............................................... 119
References ................................................. 121
6 AGC Systems Concerning Renewable Energy Sources ............ 123
6.1 An Updated AGC Frequency Response Model ............... 124
6.2 Frequency Response Analysis ........................... 128
6.3 Simulation Study ...................................... 131
6.3.1 Nine-Bus Test System ........................... 131
6.3.2 Thirty-Nine-Bus Test System .................... 133
6.4 Emergency Frequency Control and RESs .................. 138
6.5 Key Issues and New Perspectives ....................... 142
6.5.1 Need for Revision of Performance Standards ..... 142
6.5.2 Further Research Needs ......................... 144
6.6 Summary ............................................... 146
References ................................................. 146
7 AGC Design Using Multiagent Systems ........................ 149
7.1 Multiagent System (MAS): An Introduction .............. 149
7.2 Multiagent Reinforcement-Learning-Based AGC ........... 153
7.2.1 Multiagent Reinforcement Learning .............. 154
7.2.2 Area Control Agent ............................. 156
7.2.3 RL Algorithm ................................... 156
7.2.4 Application to a Thirty-Nine-Bus Test System ... 158
7.3 Using GA to Determine Actions and States .............. 161
7.3.1 Finding Individual's Fitness and Variation
Ranges ......................................... 162
7.3.2 Application to a Three-Control Area Power
System ......................................... 163
7.4 An Agent for β Estimation ............................. 165
7.5 Summary ............................................... 169
References ................................................. 169
8 Bayesian-Network-Based AGC Approach ........................ 173
8.1 Bayesian Networks: An Overview ........................ 174
8.1.1 BNs at a Glance ................................ 175
8.1.2 Graphical Models and Representation ............ 177
8.1.3 A Graphical Model Example ...................... 179
8.1.4 Inference ...................................... 182
8.1.5 Learning ....................................... 184
8.2 AGC with Wind Farms ................................... 185
8.2.1 Frequency Control and Wind Turbines ............ 185
8.2.2 Generalized ACE Signal ......................... 186
8.3 Proposed Intelligent Control Scheme ................... 187
8.3.1 Control Framework .............................. 187
8.3.2 BN Structure ................................... 188
8.3.3 Estimation of Amount of Load Change ............ 190
8.4 Implementation Methodology ............................ 193
8.4.1 BN Construction ................................ 193
8.4.2 Parameter Learning ............................. 194
8.5 Application Results ................................... 195
8.5.1 Thirty-Nine-Bus Test System .................... 195
8.5.2 A Real-Time Laboratory Experiment .............. 200
8.6 Summary ............................................... 204
References ................................................. 204
9 Fuzzy Logic and AGC Systems ................................ 207
9.1 Study Systems ......................................... 207
9.1.1 Two Control Areas with Subareas ................ 207
9.1.2 Thirty-Nine-Bus Power System ................... 208
9.2 Polar-Information-Based Fuzzy Logic AGC ............... 211
9.2.1 Polar-Information-Based Fuzzy Logic Control .... 211
9.2.2 Simulation Results ............................. 215
9.2.2.1 Trunk Line Power Control .............. 215
9.2.2.2 Control of Regulation Margin .......... 217
9.3 PSO-Based Fuzzy Logic AGC ............................. 220
9.3.1 Particle Swarm ©ptimization .................... 220
9.3.2 AGC Design Methodology ......................... 222
9.3.3 PSO Algorithm for Setting of Membership
Functions ...................................... 224
9.3.4 Application Results ............................ 224
9.4 Summary ............................................... 227
References ................................................. 228
10 Frequency Regulation Using Energy Capacitor System ......... 229
10.1 Fundamentals of the Proposed Control Scheme .......... 230
10.1.1 Restriction of Control Action (Type I) ......... 231
10.1.2 Restriction of Control Action (Type II) ........ 232
10.1.3 "Prevention of Excessive Control Action
(Type III) ..................................... 232
10.2 Study System .......................................... 233
10.3 Simulation Results 234
10.4 Evaluation of Frequency Regulation Performance ........ 236
10.5 Summary ............................................... 239
References ................................................. 240
11 Application of Genetic Algorithm in AGC Synthesis .......... 241
11.1 Genetic Algorithm: An Overview ........................ 242
11.1.1 GA Mechanism ................................... 242
11.1.2 GA in Control Systems .......................... 243
11.2 Optimal Tuning of Conventional Controllers ............ 244
11.3 Multiobjective GA ..................................... 248
11.3.1 Multiobjective Optimization .................... 248
11.3.2 Application to AGC Design ...................... 249
11.4 GA for Tracking Robust Performance Index .............. 252
11.4.1 Mixed H2/H∞ .................................... 252
11.4.2 Mixed H2/H∞ SOF Design ......................... 253
11.4.3 AGC Synthesis Using GA-Based Robust
Performance Tracking ........................... 254
11.5 GA in Learning Process ................................ 255
11.5.1 GA for Finding Training Data in a BN-Based
AGC Design ..................................... 257
11.5.2 Application Example ............................ 258
11.6 Summary ............................................... 259
References ................................................. 261
12 Frequency Regulation in Isolated Systems with Dispersed
Power Sources .............................................. 263
12.1 Configuration of Multiagent-Based AGC System .......... 264
12.1.1 Conventional AGC on Diesel Unit ................ 264
12.1.2 Coordinated AGC on the ECS and Diesel Unit ..... 264
12.2 Configuration of Laboratory System .................... 266
12.3 Experimental Results .................................. 268
12.4 Summary ............................................... 276
References ................................................. 277
Index ......................................................... 279
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