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Parallel Genetic Algorithm-Tabu Search Using PC Cluster System for Optimal Reconfiguration of Distribution Systems  

Mun Kyeong-Jun (부산대학교 전기공학과)
Song Myoung-Kee (전자부품 연구원)
Kim Hyung-Su (부산대학교 전기공학과)
Kim Chul-Hong (부산대학교 전기공학과)
Park June Ho (부산대학교 전기공학과)
Lee Hwa-Seok (거제대학 전기과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers A / v.53, no.10, 2004 , pp. 556-564 More about this Journal
Abstract
This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.
Keywords
Distribution System Reconfiguration; Genetic Algorithm; Tabu Search; PC-Cluster System; Parallel Genetic Algorithm-Tabu Search(GA-TS);
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