基于人工蜂群算法的供水泵站多目标优化与决策

Multi-objective Optimization and Decision-making of Water Supply Pump Station Based on Artificial Bee Colony Algorithm

为解决供水泵站运行效率低、能源浪费等问题,以并联离心泵站为例,建立同时考虑调度周期内泵站运行电费、机组启停次数、泵运行可靠度的多目标函数来反映泵站的综合性能,以泵总台数、转速比、供水需求为约束条件,将Pareto最优解理论引入人工蜂群算法并与多属性决策相结合,求解泵站多目标优化与决策问题。结果表明,该算法可解决供水泵站的多目标优化运行问题,减缓了机组频繁启停、提高了泵运行可靠度、降低了泵站运行电费,并为决策者提供了综合性能较好的方案。

In order to solve the problems of low operation efficiency and energy waste of water supply pump stations, taking parallel centrifugal pump stations as the research object, a multi-objective function considering the operation electricity charge of pump stations, units startup and shutdown times and the reliability of pump operation in the scheduling period was established to reflect the comprehensive performance of the pump station. Taking the total number of pumps, operating speed ratio of pump, and water supply demand as constraints, the Pareto optimal solution theory was introduced into artificial bee colony algorithm, the multi-objective optimization and decision-making problem of pump station was solved by combining with multi-attribute decision-making. The results show that the algorithm can solve the multi-objective optimal operation problem of water supply pump station, slow down the frequent start and stop of units, improve the reliability of pump operation, reduce the power charge of pump station operation, and provide a scheme with good comprehensive performance for decision-makers.