Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> In this research, reliability indicators of water distribution networks were evaluated under pipe failure conditions. The case studies included two benchmark networks and one real-life water distribution network in Iran with more hydraulic constraints. Some important reliability indicators were presented, such as resilience index, network resilience, modified resilience index, and minimum surplus head index. GANetXL was used to do the one-objective and two-objective optimization of the previously mentioned water distribution networks in order to not only minimize the cost but also maximize the reliability indicators. Moreover, the results of a statistical analysis for each pipe were used to determine the sensitive pipes that were of the most failure probability. GANetXL is an optimization tool in the Microsoft Excel environment and works based on a genetic algorithm. GANetXL has the capability of being linked to EPANET (hydraulic simulation software). The results obtained clearly showed that network resilience index was poor performance when compared with the other indexes under pipe failure conditions, especially in real-life networks that include small pipe diameters. It was also showed that if a water distribution network was optimized only in terms of cost, then there would be an unacceptable pressure drop at some nodes in case of pipe failure.
Highlights
The results shown in figure 11 demonstrate that in the cost-based optimization, surplus pressure in the nodes number 13 and 23 is less than 1m that explains these nodes are the most critical ones in the network
Both the existing pipes and hydraulic constraints were considered in the study in which GANetXL was used as the optimizer
The results of cost-oriented optimization showed that the solutions proposed by GANetXL for case study networks give solutions that are either less expensive than or as the same as the ones from literature
Summary
35 Optimal WDN design is a computationally complex problem because of its non-linear nature and the constraints involved. Finding the globally optimal solution is difficult if we use optimization methods as the non-linearity is significant. The use of discrete variables, specificsize pipe diameters, limits the quality of the optimal solution obtained. Murphy and Simpson were the first researchers who used a simple Genetic Algorithm (GA) to optimally design water distribution systems. This model was applied to determine the least cost combination of pipe diameters and rehabilitation actions 50 (Murphy and Simpson 1992). (Mohan and Babu 2009) proposed to use a 65 heuristic based approach called heuristics-based algorithm (HBA) to identify the least cost combination of pipe diameters. SMPSO used a novel factor to decrease the inertia weight of the algorithm in proportion with simulation time to facilitate both global and local search
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