Using particle swarm optimization algorithm to optimally locating and controlling of pressure reducing valves for leakage minimization in water distribution systems

Abstract

The main objective of pressure management in a water distribution system (WDS) is to minimize leakages, bursts and maintain the required pressure at every node. One of the methods for pressure management is using pressure-reducing valves (PRV). This paper outlines an optimization-simulation approach to determine the optimum location and settings of the PRVs to control the pressure and minimize the leakage in WDSs. To solve the problem, the particle swarm optimization (PSO) tool was coupled with EPANET hydraulic simulation software in MATLAB environment. The results revealed that by observing all the regulations of the problem, through utilizing the proposed method for finding optimal location and regulating the PRVs, the network average leakage rate in a 24-h utilization period dropped by 23%. The performance of the PSO-based model in pressure management was compared with models based on three specific types of powerful algorithms including a genetic algorithm (GA) from the evolutionary algorithms (EA), artificial bee colony (ABC) from the swarm intelligence, and cultural algorithm (CA) from human behavior. The PSO-based model with the lowest objective function call compared to the other three algorithms, was able to reduce leakage compared to GA, ABC, and CA by 1.63, 3.45, and 8.53%, respectively. That shows the presented method is successful in regulating the pressure level to minimize network leakage.