Reviews state-of-the-art technologies in modern heuristic optimization techniques and presents case studies showing how they have been applied in complex power and energy systems problems
Written by a team of international experts, this book describes the use of metaheuristic applications in the analysis and design of electric power systems. This includes a discussion of optimum energy and commitment of generation (nonrenewable & renewable) and load resources during day-to-day operations and control activities in regulated and competitive market structures, along with transmission and distribution systems.
Applications of Modern Heuristic Optimization Methods in Power and Energy Systems begins with an introduction and overview of applications in power and energy systems before moving on to planning and operation, control, and distribution. Further chapters cover the integration of renewable energy and the smart grid and electricity markets. The book finishes with final conclusions drawn by the editors.
Applications of Modern Heuristic Optimization Methods in Power and Energy Systems:
- Explains the application of differential evolution in electric power systems' active power multi-objective optimal dispatch
- Includes studies of optimization and stability in load frequency control in modern power systems
- Describes optimal compliance of reactive power requirements in near-shore wind power plants
- Features contributions from noted experts in the field
Ideal for power and energy systems designers, planners, operators, and consultants, Applications of Modern Heuristic Optimization Methods in Power and Energy Systems will also benefit engineers, software developers, researchers, academics, and students.
Table of Contents:
Preface xv
Contributors xvii
List of Figures xxi
List of Tables xxxiii
Chapter 1 Introduction 1
1.1 Background 1
1.2 Evolutionary Computation: A Successful Branch of CI 3
Chapter 2 Overview Of Applications In Power And Energy Systems 21
2.1 Applications to Power Systems 21
2.2 Smart Grid Application Competition Series 28
Chapter 3 Power System Planning And Operation 39
3.1 Introduction 39
3.2 Unit Commitment 40
3.3 Economic Dispatch Based on Genetic Algorithms and Particle Swarm Optimization 56
3.4 Differential Evolution in Active Power Multi-Objective Optimal Dispatch 87
3.5 Hydrothermal Coordination 106
3.6 Meta-Heuristic Method for Gms Based on Genetic Algorithm 115
3.7 Load Flow 143
3.8 Artificial Bee Colony Algorithm for Solving Optimal Power Flow 161
3.9 OPF Test Bed and Performance Evaluation of Modern Heuristic Optimization 176
3.10 Transmission System Expansion Planning 197
3.11 Conclusion 210
Chapter 4 Power System And Power Plant Control 227
4.1 Introduction 227
4.2 Load Frequency Control – Optimization and Stability 228
4.3 Control of Facts Devices 244
4.4 Hybrid of Analytical and Heuristic Techniques for facts Devices 284
4.5 Power System Automation 305
4.6 Power Plant Control 334
4.7 Predictive Control in Large-Scale Power Plant 355
4.8 Conclusion 368
Chapter 5 Distribution System 381
5.1 Introduction 381
5.2 Active Distribution Network Planning 382
5.3 Optimal Selection of Distribution System Architecture 392
5.4 Conservation Voltage Reduction Planning 418
5.5 Dynamic Distribution Network Expansion Planning with Demand Side Management 427
5.6 GA-Guided Trust-Tech Methodology for Capacitor Placement in Distribution Systems 467
5.7 Network Reconfiguration 489
5.8 Distribution System Restoration 510
5.9 Group-based PSO for System Restoration 531
5.10 MVMO for Parameter Identification of Dynamic Equivalents for Active Distribution Networks 553
5.11 Parameter Estimation of Circuit Model for Distribution Transformers 573
Chapter 6 Integration Of Renewable Energy In Smart Grid 613
6.1 Introduction 613
6.2 Renewable Energy Sources 613
6.3 Operation and Control of Smart Grid 635
6.4 Compliance of Reactive Power Requirements in Wind Power Plants 645
6.5 Photovoltaic Controller Design 667
6.6 Demand Side Management and Demand Response 680
6.7 EPSO-Based Solar Power Forecasting 691
6.8 Load Demand and Solar Generation Forecast for PV Integrated Smart Buildings 704
6.9 Multi-Objective Planning of Public Electric Vehicle Charging Stations 729
6.10 Dispatch Modeling Incorporating Maneuver Components, Wind Power, and Electric Vehicles 741
6.11 Conclusions 757
Chapter 7 Electricity Markets 775
7.1 Introduction 775
7.2 Bidding Strategies 777
7.3 Market Analysis and Clearing 781
7.4 Electricity Market Forecasting 793
7.5 Simultaneous Bidding of V2G In Ancillary Service Markets Using Fuzzy Optimization 798
7.6 Conclusions 812
References 812
Index 819
About the Author :
KWANG Y. LEE, PhD, is a Professor and Chair of Electrical and Computer Engineering at Baylor University. He is active in the Intelligent Systems Subcommittee and Station Control Subcommittee of the IEEE Power and Energy Society. He served as Editor of IEEE Transactions on Energy Conversion and Associate Editor of IEEE Transactions on Neural Networks and IFAC Journal on Control Engineering Practice.
ZITA A. VALE, PhD, is a Full Professor in the Electrical Engineering Department at the School of Engineering of the Polytechnic of Porto and Director of GECADResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development. She has published over 800 works, including more than 100 papers in international scientific journals.
