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Application of Parallel PSO Algorithm based on PC Cluster System for Solving Optimal Power Flow Problem  

Kim, Jong-Yul (한국전기연구원 전력연구단)
Moon, Kyoung-Jun (한국원자력연구원)
Lee, Haw-Seok (거제대학 전기과)
Park, June-Ho (부산대학교 전자전기통신공학부)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.56, no.10, 2007 , pp. 1699-1708 More about this Journal
Abstract
The optimal power flow(OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, the OPF problem has been intensively studied and widely used in power system operation and planning. In these days, OPF is becoming more and more important in the deregulation environment of power pool and there is an urgent need of faster solution technique for on-line application. To solve OPF problem, many heuristic optimization methods have been developed, such as Genetic Algorithm(GA), Evolutionary Programming(EP), Evolution Strategies(ES), and Particle Swarm Optimization(PSO). Especially, PSO algorithm is a newly proposed population based heuristic optimization algorithm which was inspired by the social behaviors of animals. However, population based heuristic optimization methods require higher computing time to find optimal point. This shortcoming is overcome by a straightforward parallel processing of PSO algorithm. The developed parallel PSO algorithm is implemented on a PC cluster system with 6 Intel Pentium IV 2GHz processors. The proposed approach has been tested on the IEEE 30-bus system. The results showed that computing time of parallelized PSO algorithm can be reduced by parallel processing without losing the quality of solution.
Keywords
OPF; PSO Algorithm; PC Cluster System; Parallel Processing;
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