Optimizing the cost of pumping of urban drinking water wells using the PSO metaheuristic Algorithm

The interaction effect of pumping costs and water consumption must be controlled and optimized. Supplying drinking water from underground water resources must be done according to a precise pre-designed plan so that It is optimized for both pumping and energy costs and Water should be delivered to the consumer at a reasonable price and with optimal energy consumption. In this study particle swarm metaheuristic algorithm (PSO) was used to optimize the pumping of groundwater wells that supply drinking water. The data of rate of shortage of statistic surface and the required cost were used for pumping in the Mashhad drinking water supply wells. The results show that by using the PSO algorithm, in addition to providing problem constraints, water extraction could be reduced. Results show that by keeping the number of wells the same in the current design and by applying this algorithm the cost of pumping is reduced by 4.3%. The results of sensitivity analysis also show that for a certain amount of water With a 100% increase in pumping rates with two wells, the water demand will be provided and the total costs will be reduced by about 56 percent. Also by reducing the pumping rate the number of required wells for supplying certain water needs has increased to seven and the total costs will be increased by 26 percent.