基于改进粒子群算法的水电站水库优化调度研究

Modified particle swarm optimization algorithm and its application in optimal operation of hydropower station reservoir

针对粒子群优化算法容易陷入局部最优解的问题,提出一种基于模拟退火机制的改进粒子群优化算法,并将其引入水库调度领域,设计了基于该算法的水电站水库优化调度问题的求解方法。计算实例表明,该方法采用并行搜索机制,计算速度快、全局寻优的可靠性较高,具有较好的应用前景。

Aimed at the problem of premature in particle swarm optimization（PSO） algorithm, a modified algorithm combining PSO with simulated annealing（SA） is presented in this paper. The PSO-SA（P-S） algorithm is introduced for reservoir operation, and a new method for optimal operation of hydropower station reservoir is put forward. An example shows that the PS algorithm based on parallel-searching mechanism has a better application prospects for its fast operation speed and high reliability in global optimization.