水力发电学报2012，Vol.31Issue(1)：38-44,7.
自适应混合粒子群算法在梯级水电站群优化调度中的应用
Application of self-adaptive hybrid particle swarm optimization algorithm to optimal operation of cascade reservoirs
摘要
Abstract
A self-adaptive hybrid particle swarm optimization algorithm（AHPSO） is proposed to solve the long-term optimal operation model of cascade reservoirs.With total power output as objective function,this model generates initial solutions with chaos and defines variables of particle energy,particle similarity and their thresholds to describe the algorithm＇s self-adaptive changes and the swarm-evolving degree.In the model,a random greedy searching strategy of neighborhood is adopted to overcome the shortcoming of slow evolving at the later stage.Application in a case study of the cascade reservoirs on the Lancangjiang river shows that the self-adaptive AHPSO is better in convergence and optimized solution than the traditional particle swarm method and that it is comparable to the progressive optimization algorithm but its computational cost is lower.关键词
工程水文学/梯级水电站群/优化调度/粒子群算法/自适应/粒子能量Key words
engineering hydrology/cascade reservoirs/optimal operation/particle swarm optimization/self-adaptive/particle energy分类
建筑与水利引用本文复制引用
王森,武新宇,程春田,郭有安,李红刚..自适应混合粒子群算法在梯级水电站群优化调度中的应用[J].水力发电学报,2012,31(1):38-44,7.基金项目
国家自然科学基金（50979010） 国家自然科学基金 （）
国家杰出青年科学基金 （）
