结合禁忌搜索思想的粒子群算法在乌江渡水电站厂内经济运行中的应用研究

本文针对水电站厂内经济运行中机组组合优化问题的特点,提出了一种结合禁忌搜索思想的粒子群算法(Particle Swarm Optimization,PSO).该方法采用离散二进制粒子群算法解决机组运行状态组合问题,用标准粒子群算法解决既定运行机组间负荷优化分配问题,并将两个问题结合在一起并行优化,引入禁忌搜索算法(tabular Search,TS)的记忆功能和藐视准则以提高粒子多样性,扩大搜索空间,克服PSO算法可能出现的早熟现象.以乌江渡水电站为例进行优化计算,并与PSO算法的计算结果比较,表明该方法可以有效避免早熟现象,具有较高的全局收敛能力,同时也具有较高的全局寻优能力.

An improved PSO algorithm embedded TS for economic operation of Wujiangdu hydroelectric plant

According to the features of the unit economic operation of hydroelectric plant,an improved PSO embedded tabular search is presented for solving it.The proposed method uses the discrete binary PSO and standard PSO for the units economic operiction and their combinations.The two sub-problems are run in parallel.To avoid the premature convergence phenomena,the flexible memory system of tabular search is embedded into PSO to improve particles diversity in swarm for enlarging the search space and enhancing conv...