Publisher's Synopsis
"Metaheuristics for Power System Congestion Management" is a comprehensive book that delves into the dynamic and complex field of power systems, focusing specifically on congestion management. Written by experts in the field of metaheuristics, this book presents a wide range of cutting-edge techniques and methodologies aimed at optimizing power system operations and mitigating congestion issues. The book explores the intricate interplay between power systems, algorithms, and optimization methods. It covers various aspects of power systems, including energy systems, grid networks, load balancing, transmission lines, voltage control, reactive power, and demand response. Furthermore, it addresses the challenges associated with integrating renewable energy sources into the power grid and the role of energy markets in congestion management. The authors delve into the realm of computational intelligence, discussing evolutionary algorithms, swarm intelligence, simulated annealing, genetic algorithms, particle swarm optimization, tabu search, and ant colony optimization. The book also explores the applications of artificial intelligence and machine learning techniques in power system optimization. With a strong emphasis on practicality, the book covers a wide range of topics, including power system planning, energy storage, distributed generation, demand-side management, smart grids, energy efficiency, economic dispatch, and ancillary services. It explores system stability, power system security, reliability, and resilience. The book provides a valuable resource for researchers, professionals, and students working in the field of power systems and optimization. It combines theoretical foundations with practical insights, offering optimization models and case studies to illustrate the application of metaheuristics in power system congestion management.
