自适应粒子群算法在水库优化调度中的应用研究  

Self-adaptive particle swarm optimization algorithm and its application in optimal operation of reservoirs

作　　者：刘列[1] 

机构地区：[1]广东省水文局江门水文分局,广东江门509030

出　　处：《大众科技》2017年第1期11-13,共3页Popular Science & Technology

摘　　要：针对传统粒子群算法在求解梯级水库调度问题时,容易陷入局部最优而早熟收敛的问题,提出自适应粒子群算法。该改进算法结合种群进化程度自适应调整算法控制参数,从而克服传统粒子群算法参数固定引起的搜索能力不足的问题。同时,采用种群局部重建策略解决种群进化后期多样性下降的问题。将改进的粒子群算法应用于清江梯级水电站的发电调度求解,模拟计算结果表明,文章提出的改进算法具有较强的全局寻优能力,可以进一步提高算法的搜索性能和求解精度。For the problem that particle swarm optimization algorithm often suffers being trapped in local optimum so as to be premature convergence when it is used to solve the problem of optimal operation of reservoirs, self-adaptive particle swarm optimization algorithm is proposed. The improved algorithms adaptive adjust the control parameters according to the degree of population evolution, so as to overcome the problem of insufficient search ability caused by fixed parameters. Meanwhile, population partial reconstruction strategy is used to solve the problem of decline of the species diversity in the late stage of evolution. The results of application in the Qingjiang cascade reservoirs show that the self-adaptive particle swarm optimization algorithm has strong ability of global optimization. It can further improve the search performance and precision of the algorithm.

关 键 词：水库优化调度 粒子群算法 自适应 种群局部重建 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术] TV697[水利工程—水利水电工程]