摘要
本文针对粒子群算法在求解高维、复杂的梯级水库发电优化调度时后期种群缺乏多样性、收敛于局部最优解的缺陷,结合梯级水库发电优化调度的特点,提出了应用差分演化算法改进粒子群的混合优化算法。通过实际算例验证了该混合方法的合理性和可靠性,从而为高维、复杂梯级水库发电优化调度模型求解提供了一种新的途径。
An improved particle swarm optimization（PSO）algorithm is proposed to optimize the operation of high-dimensional and complex cascade reservoirs.By adopting a differential evolution technique,this combination algorithm can preserve the variety of PSO and avoid the premature of PSO.It was verified by application to a case study and would provide a new approach to optimal operation of cascade reservoirs.
出处
《水力发电学报》
EI
CSCD
北大核心
2012年第2期33-37,164,共6页
Journal of Hydroelectric Engineering
基金
国家自然科学基金(51109189)
中国博士后科学基金资助项目(20100471007)
关键词
水电工程
梯级水库
优化调度
粒子群算法
差分演化算法
hydropower engineering
cascade reservoir
optimal operation
particle swarm optimization algorithm
differential evolution algorithm
