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论文类型：期刊论文

发表时间：2012-01-01

发表刊物：INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL

收录刊物：SCIE

卷号：15

期号：1,SI

页面范围：33-40

ISSN号：1343-4500

关键字：Cascade reservoirs; optimal operation; PSO; IPSO; DP

摘要：For solving the optimal operation problems of cascade reservoirs, an improved particle swarm optimization (IPSO) algorithm is proposed. To increase the searching efficiency, the IPSO introduces crossover operator and mutation operator, which are similar to the operators in genetic algorithm. Crossover is that the positions of the particles in solution space are making arithmetical crossover at a certain probability, and mutation is that the particles randomly make some one-dimensional component of velocity vector change into zero at a certain probability. To increase the convergence speed, the initial particle swarm generates randomly under certain conditions, and penalty function method is employed to deal with the boundary conditions and the inequality constraints. Taking cascade reservoirs for example to compare the IPSO with dynamic programming algorithm and conventional PSO, the results show that the IPSO has faster calculation speed and satisfying optimal operation results.