Abstract: Reservoir optimal scheduling is a typical multi-constrained, dynamic, non-linear optimization problem. To solve this problem, a Dynamic Programming-Particle Swarm Optimization (DP-PSO) algorithm was used to solving. This algorithm used the optimal Dynamic Programming (DP) principle to convert the reservoir optimal scheduling problem to multistage decision-making sub-problems; the solution of each sub-problem was got by particle swarm optimization algorithm. The numerical experiments show that with more time in calculation, the reliability of the DP-PSO is superior to the general DP algorithm, and the calculation time of DP-PSO is less than DP-Genetic Algorithm (DP-GA).

Key words: Reservoir Operation, particle swarm optimization algorithm, dynamic programming, dynamic programming-particle swarm optimization algorithm

摘要： 水库优化调度是一个典型的具有多约束条件的、动态的、非线性的优化问题。针对这些问题,利用动态规划-粒子群(DP-PSO)算法加以求解。利用动态规划中的多阶段最优策略原理,将水库优化调度问题转化为多阶段决策子问题,各个子问题采用粒子群算法优化求解。数值实验表明,在计算时段较多时,DP-PSO算法计算的可靠性明显优于一般的动态规划(DP)算法,在计算时间上,DP-PSO算法用时较动态规划-遗传算法(DP-GA)少。

关键词: 水库调度, 粒子群算法, 动态规划, 动态规划-粒子群算法