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Leakage Reduction in Water Distribution Systems with Efficient Placement and Control of Pressure Reducing Valves Using Soft Computing Techniques

机译:通过软计算技术有效减少配水系统的供水系统中的泄漏并控制减压阀

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Reduction of leakages in a water distribution system (WDS) is one of the major concerns of water industries. Leakages depend on pressure, hence installing pressure reducing valves (PRVs) in the water network is a successful techniques for reducing leakages. Determining the number of valves, their locations, and optimal control setting are the challenges faced. This paper presents a new algorithm-based rule for determining the location of valves in a WDS having a variable demand pattern, which results in more favorable optimization of PRV localization than that caused by previous techniques. A multiobjective genetic algorithm (NSGA-II) was used to determine the optimized control value of PRVs and to minimize the leakage rate in the WDS. Minimum required pressure was maintained at all nodes to avoid pressure deficiency at any node. Proposed methodology is applied in a benchmark WDS and after using PRVs, the average leakage rate was reduced by 6.05 l/s (20.64%), which is more favorable than the rate obtained with the existing techniques used for leakage control in the WDS. Compared with earlier studies, a lower number of PRVs was required for optimization, thus the proposed algorithm tends to provide a more cost-effective solution. In conclusion, the proposed algorithm leads to more favorable optimized localization and control of PRV with improved leakage reduction rate.
机译:减少配水系统(WDS)中的泄漏是水工业的主要关注之一。泄漏取决于压力,因此在水网络中安装减压阀(PRV)是减少泄漏的成功技术。确定阀的数量,其位置和最佳控制设置是面临的挑战。本文提出了一种新的基于算法的规则,用于确定需求模式可变的WDS中阀门的位置,与以前的技术相比,该方法可以更有利地优化PRV定位。多目标遗传算法(NSGA-II)用于确定PRV的最佳控制值,并使WDS中的泄漏率最小。在所有节点上都保持最低要求压力,以避免任何节点上的压力不足。提议的方法应用于基准WDS中,使用PRV后,平均泄漏率降低了6.05 l / s(20.64%),这比使用WDS中用于泄漏控制的现有技术获得的比率更有利。与早期的研究相比,进行优化所需的PRV数量较少,因此所提出的算法倾向于提供更具成本效益的解决方案。综上所述,所提出的算法导致PRV的更优化优化定位和控制,并提高了泄漏减少率。

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