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《Journal of Jiangsu University of Science and Technology(Natural Science Edition)》 2008-05
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Chaos genetic algorithm for shipboard power system service restoration

WANG Min,LIU Weiting(School of Electronics and Information,Jiangsu University of Science and Technology,Zhenjiang Jiangsu 212003,China)  
Fast supply restoration to the faulted sections of SPS(Shipboard Power System) is a complex and multi-object combination optimization problem.According to the characteristics of SPS,CGA(Chaos Genetic Algorithm),which combines chaos theory with GA(Genetic Algorithm),is proposed in this paper.It initializes the population of GA via chaos theory.This may hold the diversity of the individual and avoid getting stuck in local minima.Convergence rate of the algorithm is accelerated by using elitist preserved tactics,adaptive crossover and adaptive mutation.The proposed approach is applied to typical SPS fault restoration tests.The results show that the CGA algorithm can improve GA performance,speed up the convergence,and enhance the precision of restoration.Moreover,it can avoid premature convergence,and realize the SPS multi-object service restoration.
【Fund】: 国防预研基金资助项目(2006DX010G)
【CateGory Index】: U665
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