Power System Optimization

1 - Cover [Seite 1]
2 - Title Page [Seite 5]
3 - Copyright [Seite 6]
4 - Dedication [Seite 7]
5 - Contents [Seite 13]
6 - Foreword [Seite 19]
7 - Preface [Seite 21]
8 - Acknowledgments [Seite 27]
9 - List of Figures [Seite 29]
10 - List of Tables [Seite 33]
11 - Acronyms [Seite 37]
12 - Symbols [Seite 41]
13 - Chapter 1 Introduction [Seite 43]
13.1 - 1.1 Power System Optimal Planning [Seite 44]
13.1.1 - 1.1.1 Generation Expansion Planning [Seite 45]
13.1.2 - 1.1.2 Transmission Expansion Planning [Seite 47]
13.1.3 - 1.1.3 Distribution System Planning [Seite 49]
13.2 - 1.2 Power System Optimal Operation [Seite 50]
13.2.1 - 1.2.1 Unit Commitment and Hydrothermal Scheduling [Seite 50]
13.2.2 - 1.2.2 Economic Dispatch [Seite 54]
13.2.3 - 1.2.3 Optimal Load Flow [Seite 56]
13.3 - 1.3 Power System Reactive Power Optimization [Seite 58]
13.4 - 1.4 Optimization in Electricity Markets [Seite 60]
13.4.1 - 1.4.1 Strategic Participants' Bids [Seite 60]
13.4.2 - 1.4.2 Market Clearing Model [Seite 62]
13.4.3 - 1.4.3 Market Equilibrium Problem [Seite 63]
14 - Chapter 2 Theories and Approaches of Large-Scale Complex Systems Optimization [Seite 64]
14.1 - 2.1 Basic Theories of Large-scale Complex Systems [Seite 65]
14.1.1 - 2.1.1 Hierarchical Structures of Large-scale Complex Systems [Seite 66]
14.1.2 - 2.1.2 Basic Principles of Coordination [Seite 69]
14.1.3 - 2.1.3 Decomposition and Coordination of Large-scale Systems [Seite 70]
14.2 - 2.2 Hierarchical Optimization Approaches [Seite 72]
14.3 - 2.3 Lagrangian Relaxation Method [Seite 78]
14.4 - 2.4 Cooperative Coevolutionary Approach for Large-scale Complex System Optimization [Seite 82]
14.4.1 - 2.4.1 Framework of Cooperative Coevolution [Seite 83]
14.4.2 - 2.4.2 Cooperative Coevolutionary Genetic Algorithms and the Numerical Experiments [Seite 85]
14.4.3 - 2.4.3 Basic Theories of CCA [Seite 87]
14.4.4 - 2.4.4 CCA's Potential Applications in Power Systems [Seite 88]
15 - Chapter 3 Optimization Approaches in Microeconomics and Game Theory [Seite 91]
15.1 - 3.1 General Equilibrium Theory [Seite 93]
15.1.1 - 3.1.1 Basic Model of a Competitive Economy [Seite 94]
15.1.2 - 3.1.2 Walrasian Equilibrium [Seite 95]
15.1.3 - 3.1.3 First and Second Fundamental Theorems of Welfare Economics [Seite 96]
15.2 - 3.2 Noncooperative Game Theory [Seite 97]
15.2.1 - 3.2.1 Representation of Games [Seite 97]
15.2.2 - 3.2.2 Existence of Equilibrium [Seite 102]
15.3 - 3.3 Mechanism Design [Seite 103]
15.3.1 - 3.3.1 Principles of Mechanism Design [Seite 103]
15.3.2 - 3.3.2 Optimization of a Single Commodity Auction [Seite 105]
15.4 - 3.4 Duality Principle and Its Economic Implications [Seite 108]
15.4.1 - 3.4.1 Economic Implication of Linear Programming Duality [Seite 108]
15.4.2 - 3.4.2 Economic Implication of Duality in Nonlinear Programming [Seite 110]
15.4.3 - 3.4.3 Economic Implication of Lagrangian Relaxation Method [Seite 113]
16 - Chapter 4 Power System Planning [Seite 118]
16.1 - 4.1 Generation Planning Based on Lagrangian Relaxation Method [Seite 118]
16.1.1 - 4.1.1 Problem Formulation [Seite 120]
16.1.2 - 4.1.2 Lagrangian Relaxation for Generation Investment Decision [Seite 122]
16.1.3 - 4.1.3 Probabilistic Production Simulation [Seite 127]
16.1.4 - 4.1.4 Example [Seite 129]
16.1.5 - 4.1.5 Summary [Seite 133]
16.2 - 4.2 Transmission Planning Based on Improved Genetic Algorithm [Seite 133]
16.2.1 - 4.2.1 Mathematical Model [Seite 135]
16.2.2 - 4.2.2 Improvements of Genetic Algorithm [Seite 137]
16.2.3 - 4.2.3 Example [Seite 138]
16.2.4 - 4.2.4 Summary [Seite 143]
16.3 - 4.3 Transmission Planning Based on Ordinal Optimization [Seite 145]
16.3.1 - 4.3.1 Introduction [Seite 145]
16.3.2 - 4.3.2 Transmission Expansion Planning Problem [Seite 146]
16.3.3 - 4.3.3 Ordinal Optimization [Seite 149]
16.3.4 - 4.3.4 Crude Model for Transmission Planning Problem [Seite 153]
16.3.5 - 4.3.5 Example [Seite 154]
16.3.6 - 4.3.6 Summary [Seite 162]
16.4 - 4.4 Integrated Planning of Distribution Systems Based on Hybrid Intelligent Algorithm [Seite 163]
16.4.1 - 4.4.1 Mathematical Model of Integrated Planning Based on DG and DSR [Seite 164]
16.4.2 - 4.4.2 Hybrid Intelligent Algorithm [Seite 166]
16.4.3 - 4.4.3 Example [Seite 167]
16.4.4 - 4.4.4 Summary [Seite 171]
17 - Chapter 5 Power System Operation [Seite 173]
17.1 - 5.1 Unit Commitment Based on Cooperative Coevolutionary Algorithm [Seite 173]
17.1.1 - 5.1.1 Problem Formulation [Seite 174]
17.1.2 - 5.1.2 Cooperative Coevolutionary Algorithm [Seite 175]
17.1.3 - 5.1.3 Form Primal Feasible Solution Based on the Dual Results [Seite 180]
17.1.4 - 5.1.4 Dynamic Economic Dispatch [Seite 182]
17.1.5 - 5.1.5 Example [Seite 188]
17.1.6 - 5.1.6 Summary [Seite 190]
17.2 - 5.2 Security-Constrained Unit Commitment with Wind Power Integration Based on Mixed Integer Programming [Seite 191]
17.2.1 - 5.2.1 Suitable SCUC Model for MIP [Seite 193]
17.2.2 - 5.2.2 Selection of St and the Significance of Extreme Scenarios [Seite 196]
17.2.3 - 5.2.3 Example [Seite 198]
17.2.4 - 5.2.4 Summary [Seite 202]
17.3 - 5.3 Optimal Power Flow with Discrete Variables Based on Hybrid Intelligent Algorithm [Seite 202]
17.3.1 - 5.3.1 Formulation of OPF Problem [Seite 204]
17.3.2 - 5.3.2 Modern Interior Point Algorithm (MIP) [Seite 205]
17.3.3 - 5.3.3 Genetic Algorithm with Annealing Selection (AGA) [Seite 209]
17.3.4 - 5.3.4 Flow of Presented Algorithm [Seite 211]
17.3.5 - 5.3.5 Example [Seite 211]
17.3.6 - 5.3.6 Summary [Seite 214]
17.4 - 5.4 Optimal Power Flow with Discrete Variables Based on Interior Point Cutting Plane Method [Seite 215]
17.4.1 - 5.4.1 IPCPM and Its Analysis [Seite 217]
17.4.2 - 5.4.2 Improvement of IPCPM [Seite 222]
17.4.3 - 5.4.3 Example [Seite 227]
17.4.4 - 5.4.4 Summary [Seite 229]
18 - Chapter 6 Power System Reactive Power Optimization [Seite 231]
18.1 - 6.1 Space Decoupling for Reactive Power Optimization [Seite 231]
18.1.1 - 6.1.1 Multi-agent System-based Volt/VAR Control [Seite 232]
18.1.2 - 6.1.2 Coordination Optimization Method [Seite 235]
18.2 - 6.2 Time Decoupling for Reactive Power Optimization [Seite 240]
18.2.1 - 6.2.1 Cost Model of Adjusting the Control Devices of Volt/VAR Control [Seite 244]
18.2.2 - 6.2.2 Time-Decoupling Model for Reactive Power Optimization Based upon Cost of Adjusting the Control Devices [Seite 249]
18.3 - 6.3 Game Theory Model of Multi-agent Volt/VAR Control [Seite 257]
18.3.1 - 6.3.1 Game Mechanism of Volt/VAR Control During Multi-level Power Dispatch [Seite 259]
18.3.2 - 6.3.2 Payoff Function Modeling of Multi-agent Volt/VAR Control [Seite 266]
18.4 - 6.4 Volt/VAR Control in Distribution Systems Using an Approach Based on Time Interval [Seite 273]
18.4.1 - 6.4.1 Problem Formulation [Seite 275]
18.4.2 - 6.4.2 Load Level Division [Seite 276]
18.4.3 - 6.4.3 Optimal Dispatch of OLTC and Capacitors Using Genetic Algorithm [Seite 278]
18.4.4 - 6.4.4 Example [Seite 280]
18.4.5 - 6.4.5 Summary [Seite 286]
19 - Chapter 7 Modeling and Analysis of Electricity Markets [Seite 289]
19.1 - 7.1 Oligopolistic Electricity Market Analysis Based on Coevolutionary Computation [Seite 289]
19.1.1 - 7.1.1 Market Model Formulation [Seite 291]
19.1.2 - 7.1.2 Electricity Market Analysis Based on Coevolutionary Computation [Seite 294]
19.1.3 - 7.1.3 Example [Seite 300]
19.1.4 - 7.1.4 Summary [Seite 307]
19.2 - 7.2 Supply Function Equilibrium Analysis Based on Coevolutionary Computation [Seite 307]
19.2.1 - 7.2.1 Market Model Formulation [Seite 309]
19.2.2 - 7.2.2 Coevolutionary Approach to Analyzing SFE Model [Seite 313]
19.2.3 - 7.2.3 Example [Seite 315]
19.2.4 - 7.2.4 Summary [Seite 325]
19.3 - 7.3 Searching for Electricity Market Equilibrium with Complex Constraints Using Coevolutionary Approach [Seite 326]
19.3.1 - 7.3.1 Market Model Formulation [Seite 328]
19.3.2 - 7.3.2 Coevolutionary Computation [Seite 332]
19.3.3 - 7.3.3 Example [Seite 334]
19.3.4 - 7.3.4 Summary [Seite 343]
19.4 - 7.4 Analyzing Two-Settlement Electricity Market Equilibrium by Coevolutionary Computation Approach [Seite 343]
19.4.1 - 7.4.1 Market Model Formulation [Seite 345]
19.4.2 - 7.4.2 Coevolutionary Approach to Analyzing Market Model [Seite 349]
19.4.3 - 7.4.3 Example [Seite 351]
19.4.4 - 7.4.4 Summary [Seite 360]
20 - Chapter 8 Future Developments [Seite 361]
20.1 - 8.1 New Factors in Power System Optimization [Seite 362]
20.1.1 - 8.1.1 Planning and Investment Decision Under New Paradigm [Seite 362]
20.1.2 - 8.1.2 Scheduling/Dispatch of Renewable Energy Sources [Seite 363]
20.1.3 - 8.1.3 Energy Storage Problems [Seite 364]
20.1.4 - 8.1.4 Environmental Impact [Seite 365]
20.1.5 - 8.1.5 Novel Electricity Market [Seite 365]
20.2 - 8.2 Challenges and Possible Solutions in Power System Optimization [Seite 366]
21 - Appendix [Seite 370]
21.1 - A.1 Header File [Seite 370]
21.2 - A.2 Species Class [Seite 371]
21.3 - A.3 Ecosystem Class [Seite 377]
21.4 - A.4 Main Function [Seite 378]
22 - References [Seite 380]
23 - Index [Seite 395]
24 - EULA [Seite 403]