Robust Design Of Facts Controller Using AI Technique » książka
Robust Design Of Facts Controller Using AI Technique
ISBN-13: 9783659371998 / Angielski / Miękka / 2013 / 80 str.
Recent development of power electronics introduces the use of Flexible AC Transmission System (FACTS) controllers in power systems. FACTS controllers are capable of controlling the network condition in a very fast manner and this unique feature of FACTS can be exploited to improve the stability of a power system. Static Synchronous Series Compensator (SSSC) is one of the important members of FACTS family that is increasingly applied by the utilities in modern power systems with long transmission lines. In recent years, one of the most promising research field has been "Heuristics from Nature," an area utilizing analogies with nature or social systems. Among these heuristic techniques, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) techniques appeared as promising algorithms for handling the optimization problems. Optimization techniques such as GA, PSO and DE are inspired by nature, and have proved themselves to be effective solutions to optimization problems. Among the modern heuristic optimization techniques, the GA algorithm is quite popular among the researchers.
Recent development of power electronics introduces the use of Flexible AC Transmission System (FACTS) controllers in power systems. FACTS controllers are capable of controlling the network condition in a very fast manner and this unique feature of FACTS can be exploited to improve the stability of a power system. Static Synchronous Series Compensator (SSSC) is one of the important members of FACTS family that is increasingly applied by the utilities in modern power systems with long transmission lines. In recent years, one of the most promising research field has been "Heuristics from Nature", an area utilizing analogies with nature or social systems. Among these heuristic techniques, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) techniques appeared as promising algorithms for handling the optimization problems. Optimization techniques such as GA, PSO and DE are inspired by nature, and have proved themselves to be effective solutions to optimization problems. Among the modern heuristic optimization techniques, the GA algorithm is quite popular among the researchers.
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