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Optimal pump operation for water distribution systems using a new multi-agent Particle Swarm Optimization technique with EPANET

机译:使用带有EPANET的新型多代理粒子群优化技术,对供水系统进行最佳泵操作

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摘要

The optimal pump scheduling allows for computing the most economical energy costs and provides more efficient operations for complex water distribution systems (WDS) with multiple pumping stations. The proposed technique employs the latest advances in multi-agent Particle Swarm Optimization (MOPSO) to automatically determine the most cost-effective solutions for scheduling/operation multiple pumps in multiple pumping stations, while satisfying both loading conditions and hydraulic performance requirements. The present work considers a bi-objective pump-scheduling problem, where the objectives are: minimize the electrical energy cost ($/KW.h) and minimize the maintenance costs in terms of the total number of pump switches. In additional to the bi-objective pump-operational problem, pressure and tank levels (i.e., initial, minimum, and maximum) are considered as constraints in this paper for computing the most cost-effective solutions. The constraint-handling method, the Modified MOPSO (M-MOPSO) algorithm, and the modified EPANET Toolkit 2.0 are used to solve the constrained multi-objective problem. The results showed that the new MOPSO algorithm produced the most economical pump scheduling solutions.
机译:最佳的泵调度可以计算出最经济的能源成本,并为具有多个泵站的复杂水分配系统(WDS)提供更高效的运行。所提出的技术利用多智能体粒子群优化(MOPSO)的最新进展来自动确定在多个泵站中调度/操作多个泵的最经济有效的解决方案,同时满足装载条件和液压性能要求。当前的工作考虑了一个双目标泵调度问题,其目标是:以泵开关总数为单位,将电能成本($ / KW.h)降至最低,并将维护成本降至最低。除了双目标泵操作问题外,本文中还考虑了压力和油箱液位(即初始,最小和最大)作为计算最具成本效益的解决方案的约束。约束处理方法,改进的MOPSO(M-MOPSO)算法和改进的EPANET Toolkit 2.0用于解决受约束的多目标问题。结果表明,新的MOPSO算法产生了最经济的泵调度解决方案。

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