基于TIPSO的水电站优化调度研究  

Study on Hydropower Station Optimal Operation Under Electricity Market Environment Based on Two-Layer Improved Particle Swarm Optimization

作　　者：陈学义 方国华[1] 吴承君 CHEN Xueyi;FANG Guohua;WU Chengjun(College of Water Conservancy and Hydropower,Hohai University,Nanjing 210098,China)

机构地区：[1]河海大学水利水电学院,江苏南京210098

出　　处：《人民黄河》2020年第6期58-62,67,共6页Yellow River

基　　金：湖南省水利科技项目(〔2015〕245-13);湖南省水利科技重点项目(湘水科计〔2016〕194-21)。

摘　　要：针对水电站多目标联合优化调度问题,提出双层改进粒子群算法(TIPSO)。该算法通过动态廊道约束,提高粒子群算法中粒子初始解的质量;通过改进动态权重系数,增强粒子群算法在前期的全局寻优能力和后期的局部寻优能力,提高粒子群算法的收敛性。将该算法应用于求解河南省陆浑水电站多目标优化调度问题,计算结果表明双层改进粒子群算法具有较好的收敛性能;通过与动态规划算法计算结果对比,表明该算法求解高维、复杂、多约束问题的可靠性和有效性。Aiming at the multi-objective optimal operation of hydropower station, a two-layer improved particle swarm optimization algorithm(TIPSO) was proposed. The TIPSO increased the quality of initial solution in particle swarm optimization through dynamic corridor constraint. By improving the dynamic weight coefficient, TIPSO could improve the global optimization ability in the early stage and the local optimization ability in the late stage. It improved the convergence of particle swarm optimization. The TIPSO was applied to the multi-objective optimization operation of Luhun Hydropower Station in Henan Province. The results show that TIPSO has better convergence performance. Compared with the results of the dynamic programming algorithm, it shows that the algorithm is reliable and effective in solving high-dimensional, complex and multi-constrained issues.

关 键 词：水电站 优化调度 多目标优化 粒子群算法 

分 类 号：TV213.4[水利工程—水文学及水资源]