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

  • A. Gupta Electronics and Communication Dpt, Visvesvaraya National Institute of Technology, Nagpur, India
  • N. Bokde Electronics and Communication Dpt, Visvesvaraya National Institute of Technology, Nagpur, India
  • D. Marathe Electronics and Communication Dpt, Visvesvaraya National Institute of Technology, Nagpur, India
  • K. Kulat Electronics and Communication Dpt, Visvesvaraya National Institute of Technology, Nagpur, India
Volume: 7 | Issue: 2 | Pages: 1528-1534 | April 2017 | https://doi.org/10.48084/etasr.1032

Abstract

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.

Keywords: leakage, pressure management, multiobjective genetic algorithm, pressure reducing valves, water distribution system

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