Applications of Modern Heuristic Optimization Methods in Power and Energy Systems
IEEE Press Series on Power Engineering
1. Edition April 2020
896 Pages, Hardcover
Wiley & Sons Ltd
Further versions
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.
Contributors
List of Figures
List of Tables
1. Introduction
References
2. Overview of Applications in Power and Energy Systems
References
3. Power System Planning and Operation
3.1 Introduction
3.2 Unit Commitment
3.3 Economic Dispatch Based on Genetic Algorithms and Particle Swarm Optimization
3.4 Differential Evolution in Active Power Multi-objective Optimal Dispatch
3.5 Hydro-Thermal Coordination
3.6 Generator Maintenance Scheduling Based on Genetic Algorithm
3.7 Load Flow
3.8 Artificial Bee Colony Algorithm for Solving Optimal Power Flow
3.9 OPF Test Bed and Performance Evaluation of Modern Heuristic Optimization
3.10 Transmission System Expansion Planning
3.11 Conclusions
References
4. Power System and Power Plant Control
4.1 Introduction
4.2 Voltage Control
4.3 Load Frequency Control - Optimization and Stability
4.4 Control of FACTS Devices
4.5 Hybrid of Analytical and Heuristic Techniques for FACTS Devices
4.6 Power System Automation
4.7 Power Plant Control
4.8 Predictive Control in Large-Scale Power Plant
4.9 Industrial Power Plant Control
4.10 Conclusions
References
5. Distribution System
5.1 Introduction
5.2 Active Distribution Network Planning
5.3 Optimal Selection of Distribution System Architecture
5.4 Conservation Voltage Reduction Planning
5.5 Dynamic Distribution Network Expansion Planning with Demand Side Management
5.6 GA-Guided Trust-Tech Methodology for Capacitor Placement in Distribution Systems
5.7 Network Reconfiguration
5.8 Distribution System Restoration
5.9 Group-based PSO for System Restoration
5.10 MVMO for Parameter Identification of Dynamic Equivalents for Active Distribution Networks
5.11 Parameter Estimation of Circuit Model for Distribution Transformers
5.12 Conclusions
References
6. Integration of Renewable Energy in Smart Grid
6.1 Introduction
6.2 Renewable Energy Sources
6.3 Operation and Control of Smart Grid
6.4 Compliance of Reactive Power Requirements in Wind Power Plants
6.5 Photovoltaic Controller Design
6.6 Demand Side Management and Demand Response
6.7 EPSO-based Solar Power Forecasting
6.8 Load Demand and Solar Generation Forecast for PV Integrated Smart Buildings
6.9 Multi-objective Planning of Public Electric Vehicle Charging Stations
6.10 Dispatch Modeling Incorporating Maneuver Components, Wind Power and Electric Vehicles
6.11 Conclusions
References
7. Electricity Markets
7.1 Introduction
7.2 Bidding Strategies
7.3 Market Analysis and Clearing
7.4 Electricity Market Forecasting
7.5 Simultaneous Bidding of V2G in Ancillary Service Markets Using Fuzzy Optimization
7.6 Conclusions
References
Index
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 GECAD--Research 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.
