基于粒子群算法的梯级泵站优化调度研究

Optimal Scheduling of Multistage Pumping Stations Based on Particles Swarm Optimization

针对大型梯级泵站运行特点,用调度周期内的机组启动次数衡量维修成本,建立以抽水电费最小和机组启动次数最少为优化目标、以调度周期不同时段下流量分配为决策变量的双目标优化调度模型,并利用线性加权方法评估双目标之间的关系,最终采用粒子群求解算法进行模型求解。工程实例分析表明,基于线性加权的梯级泵站双目标优化调度,不仅可以获得抽水电费与机组启动次数之间的权重关系和最优运行方案,也可为梯级泵站调度决策提供理论依据。

The mathematical model was established to optimize the scheduling of multistage pumping stations,which used the minimum pumping costs and the minimum start- up times of units as the optimal objectives. And then the particles swarm optimization combined with the linear weighting method was used to solve the optimal scheduling model. The research results show that this optimal model can reveal the internal relationship between pumping costs and maintenance costs easily and it also acquire the optimal scheduling,so it is helpful to make the scheduling of multistage pumping stations.