Maximizing the coverage of quality sensors in the water distribution network (case studies: Lee and Deininger and the second and the third EPANET networks)

• The optimal location and number of the sensor in water distribution networks is determined using dragonfly algorithm (DA). • The EPANET software is used as a simulator model that is linked with MATLAB software. • The obtained results are compared with the results of genetic algorithm (GA). • Lee and Deininger and second and third network examples of EPANET are selected as case studies. • By using the DA, the WDN nodal coverage values of all case studies are increased by about 37.7 % compared to GA. Due to the sensitivity of water quality to all types of pollution (intentional and unintentional), monitor of drinking Water distribution networks (WDNs) is necessary. Therefore, the optimal location of quality sensors should be defined to increase the sensors coverage of consumption nodes in the WDN. For this purpose, in this research, the best location and the number of sensors are determined by modeling it as optimization. Three benchmark problems are used. Here, the Dragonfly Algorithm (DA) is used to solve optimization problem considering different scenarios for three case studies, including Lee and Deininger and the second and the third EPANET networks. The obtained results are compared with genetic algorithm (GA). For the Lee and Deininger network, by using the DA, the nodal coverage values are increased by 8.34 %, 8.33 %, 2.5 %, and 17.5 % compared to GA, for the first, second, third and forth scenarios, respectively. In addition, for the second (third) network example of EPANET software, by using DA, the nodal coverage values are increased by 83.03 % (17.22 %) and 93.36 % (71.33 %) compared to GA, for first and second scenarios, respectively.