摘要
提出基于混合粒子群优化(PSO)算法求解流域梯级单目标优化调度问题方法的一般结构,并对三峡梯级的发电和洪水优化调度问题进行了研究。该算法利用离散微分动态规划法(DDDP)算法对粒子群优化算法的gBest粒子进行二次寻优,加快了算法的收敛速度和精度。
Based on hybrid Particle Swarm Optimization （PSO）, a general algorithm frame is proposed for the purpose of solving single-objective optimal generation and flood regulation of cascade hydropower plants, and the problem of Three Gorges cascaded optimal regulation is studied. The proposed algorithm employs discrete differential dynamic programming （DDDP） as optimizer of the gBest in the evolution process to accelerate the convergence,
出处
《水力发电》
北大核心
2007年第10期86-88,共3页
Water Power
基金
中国博士后科学基金资助项目(2004034473)
关键词
梯级调度
优化
粒子群优化算法
cascade regulation
optimization
particle swarm optimization
