Modern Heuristic Optimization Techniques

Kwang Y. Lee, PhD, is a Professor and Chair of Electrical and Computer Engineering at Baylor University (Texas). He is a Fellow of the IEEE. He was an associate editor of IEEE Transactions on Neural Networks and is an Editor of IEEE Transactions on Energy Conversion. He was also a member of the board of directors of the International Conference on Intelligent System Applications to Power Systems (ISAP).Mohamed A. El-Sharkawi, PhD, is a Professor of Electrical Engineering at the University of Washington. He is a Fellow of the IEEE, founder of the International Forum on the Application of Neural Networks to Power Systems (ANNPS), and cofounder of the International Conference on Intelligent System Applications to Power Systems (ISAP).

• Preface xxiContributors xxviiPart 1 Theory of Modern Heuristic Optimization 11 Introduction to Evolutionary Computation 3David B. Fogel1.1 Introduction 31.2 Advantages of Evolutionary Computation 41.3 Current Developments 121.4 Conclusions 192 Fundamentals of Genetic Algorithms 25Alexandre P. Alves da Silva and Djalma M. Falcao2.1 Introduction 252.2 Modern Heuristic Search Techniques 252.3 Introduction to GAs 272.4 Encoding 282.5 Fitness Function 302.6 Basic Operators 332.7 Niching Methods 382.8 Parallel Genetic Algorithms 392.9 Final Comments 403 Fundamentals of Evolution Strategies and Evolutionary Programming 43Vladimiro Miranda3.1 Introduction 433.2 Evolution Strategies 463.3 Evolutionary Programming 603.4 Common Features 633.5 Conclusions 684 Fundamentals of Particle Swarm Optimization Techniques 71Yoshikazu Fukuyama4.1 Introduction 714.2 Basic Particle Swarm Optimization 724.3 Variations of Particle Swarm Optimization 764.4 Research Areas and Applications 824.5 Conclusions 835 Fundamentals of Ant Colony Search Algorithms 89Yong-Hua Song, Haiyan Lu, Kwang Y. Lee, and I. K. Yu5.1 Introduction 895.2 Ant Colony Search Algorithm 905.3 Conclusions 996 Fundamentals of Tabu Search 101Alcir J. Monticelli, Rubén Romero, and Eduardo Nobuhiro Asada6.1 Introduction 1016.2 Functions and Strategies in Tabu Search 1106.3 Applications of Tabu Search 1196.4 Conclusions 1207 Fundamentals of Simulated Annealing 123Alcir J. Monticelli, Rubén Romero, and Eduardo Nobuhiro Asada7.1 Introduction 1237.2 Basic Principles 1257.3 Cooling Schedule 1277.4 SA Algorithm for the Traveling Salesman Problem 1317.5 SA for Transmission Network Expansion Problem 1347.6 Parallel Simulated Annealing 1407.7 Applications of Simulated Annealing 1437.8 Conclusions 1448 Fuzzy Systems 147Germano Lambert-Torres8.1 Motivation and Definitions 1478.2 Integration of Fuzzy Systems with Evolutionary Techniques 1508.3 An Illustrative Example of a Hybrid System 1528.4 Conclusions 1679 Differential Evolution, an Alternative Approach to Evolutionary Algorithm 171Kit Po Wong and ZhaoYang Dong9.1 Introduction 1719.2 Evolutionary Algorithms 1729.3 Differential Evolution 1769.4 Key Operators for Differential Evolution 1819.5 An Optimization Example 1849.6 Conclusions 18610 Pareto Multiobjective Optimization 189Patrick N. Ngatchou, Anahita Zarei, Warren L. J. Fox, and Mohamed A. El-Sharkawi10.1 Introduction 18910.2 Basic Principles 19010.3 Solution Approaches 19410.4 Performance Analysis 20210.5 Conclusions 20511 Trust-Tech Paradigm for Computing High-Quality Optimal Solutions: Method and Theory 209Hsiao-Dong Chiang and Jaewook Lee11.1 Introduction 20911.2 Problem Preliminaries 21011.3 A Trust-Tech Paradigm 21311.4 Theoretical Analysis of Trust-Tech Method 21811.5 A Numerical Trust-Tech Method 22111.6 Hybrid Trust-Tech Methods 22511.7 Numerical Schemes 22711.8 Numerical Studies 22811.9 Conclusions Remarks 231Part 2 Selected Applications of Modern Heuristic Optimization In Power Systems 23512 Overview of Applications in Power Systems 237Alexandre P. Alves da Silva, Djalma M. Falcão, and Kwang Y. Lee12.1 Introduction 23712.2 Optimization 23712.3 Power System Applications 23812.4 Model Identification 23912.5 Control 24212.6 Distribution System Applications 24412.7 Conclusions 24913 Application of Evolutionary Technique to Power System Vulnerability Assessment 261Mingoo Kim, Mohamed A. El-Sharkawi, Robert J. Marks, and Ioannis N. Kassabalidis13.1 Introduction 26113.2 Vulnerability Assessment and Control 26313.3 Vulnerability Assessment Challenges 26413.4 Conclusions 28114 Applications to System Planning 285Eduardo Nobuhiro Asada, Youngjae Jeon, Kwang Y. Lee, Vladimiro Miranda, Alcir J. Monticelli, Koichi Nara, Jong-Bae Park, Rubén Romero, and Yong-Hua Song14.1 Introduction 28514.2 Generation Expansion 28614.3 Transmission Network Expansion 29714.4 Distribution Network Expansion 31114.5 Reactive Power Planning at Generation–Transmission Level 32014.6 Reactive Power Planning at Distribution Level 32614.7 Conclusions 33015 Applications to Power System Scheduling 337Koay Chin Aik, Loi Lei Lai, Kwang Y. Lee, Haiyan Lu, Jong-Bae Park, Yong-Hua Song, Dipti Srinivasan, John G. Vlachogiannis, and I. K. Yu15.1 Introduction 33715.2 Economic Dispatch 33715.3 Maintenance Scheduling 35415.4 Cogeneration Scheduling 36615.5 Short-Term Generation Scheduling of Thermal Units 38015.6 Constrained Load Flow Problem 38516 Power System Controls 403Yoshikazu Fukuyama, Hamid Ghezelayagh, Kwang Y. Lee, Chen-Ching Liu, Yong-Hua Song, and Ying Xiao16.1 Introduction 40316.2 Power System Controls: Particle Swarm Technique 40416.3 Power Plant Controller Design with GA 41716.4 Evolutionary Programming Optimizer and Application in Intelligent Predictive Control 42716.5 An Interactive Compromise Programming-Based MO Approach to FACTS Control 44417 Genetic Algorithms for Solving Optimal Power Flow Problems 471Loi Lei Lai and Nidul Sinha17.1 Introduction 47117.2 Genetic Algorithms 47317.3 Load Flow Problem 47817.4 Optimal Power Flow Problem 48317.5 OPF with FACTS Devices 48817.6 Conclusions 49918 An Interactive Compromise Programming-Based Multiobjective Approach to FACTS Control 501Ying Xiao, Yong-Hua Song, and Chen-Ching Liu18.1 Introduction 50118.2 Review of Multiobjective Optimization Techniques 50318.3 Formulated MO Optimization Model 50618.4 Proposed Interactive Displaced Worst Compromise Programming Method 51118.5 Proposed Interactive Procedure with WC Displacement 51318.6 Implementation 51618.7 Numerical Results 51618.8 Conclusions 52119 Hybrid Systems 525Vladimiro Miranda19.1 Introduction 52519.2 Capacitor Sizing and Location and Analytical Sensitivities 52719.3 Unit Commitment Fuzzy Sets and Cleverer Chromosomes 53819.4 Voltage/Var Control and Loss Reduction in Distribution Networks with an Evolutionary Self-Adaptive Particle Swarm Optimization Algorithm: EPSO 55019.5 Conclusions 559References 560Index 563

This text provides excellent, expert level, treatment of a very important systems engineering topic that will benefit students and practicing engineers. (IEEE Power Electronics Society Newsletter, 3rd Quarter, 2008)