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Optimal Pump Scheduling to Pressure Management for Large-Scale Water Distribution Systems

机译:大型水分配系统压力管理的最佳泵调度

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摘要

Water loss is a global problem. Water loss in leakages in water distribution systems (WDSs) can be significantly reduced as pressures at outlets of pumping stations are optimized. Due to the introduction of binary variables for describing on/off operations of pumps, the optimal pressure management is formulated as a large-scale mixed integer nonlinear programming (MINLP) problem which is extremely difficult to be solved by MINLP algorithms. Many studies have employed meta-heuristic algorithms to solve such the MINLP problem, but only applied for small-scale networks and it took an expensive computation time. This paper develops an efficient formulation of MINLP for optimal pressure managing problem. It is due to the fact that the large-scale MINLP can be decomposed into small-scaled MINLPs, hence it can be solved efficiently by MINLP solvers based gradient methods in an reasonable computation time. To demonstrate the efficiency of our solution approach, the real-world water distribution systems in Thainguyen city in Vietnam will be considered for optimization of pressure management. The resulted pumping schedules lead to higher reduction of excessive pressures and water leakage amounts in comparison with those by the current pumping schedule.
机译:水分损失是一个全球问题。随着泵站出口的压力优化,水分配系统(WDS)泄漏中的漏水损失可显着降低。由于引入了用于描述泵的ON / OFF操作的二进制变量,最佳压力管理被制定为大规模混合整数非线性编程(MINLP)问题,这非常难以通过MINLP算法解决。许多研究采用了Meta-heuristic算法来解决此类MINLP问题,而是仅适用于小规模网络,并且拍摄了昂贵的计算时间。本文开发了MINLP的有效配方,以获得最佳压力管理问题。这是由于大规模的Minlp可以分解成小尺寸的Minlps,因此可以在合理的计算时间中基于MINLP求解器基于梯度方法有效地解决。为了展示我们解决方案方法的效率,将考虑越南Thainguyen City的现实世界水分配系统,以便优化压力管理。与当前泵送时间表相比,所产生的泵送调度导致过度压力和漏水量的过度压力和漏水量更高。

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