Optimization of Water Distribution Network Demand Patterns Using Real-Coded Genetic Algorithms

Abstract

The penetration rate of water supply via water supply facilities in the Republic of Korea has reached 99%, with 94% of the energy for operation consumed by pumps transporting water. Consequently, developing efficient pump operation techniques is crucial for reducing energy costs in water supply systems. This study employs real-coded genetic algorithm techniques to compute optimized demand patterns, considering the utilization of water tanks within networks. Hydraulic appropriateness is verified by evaluating pressure within nodes determined by derived patterns through numerical analysis simulations. Furthermore, after calculating flows supplied to the networks, pump power is determined, and resultant energy costs are estimated to evaluate economic feasibility. Results indicate that pressure distribution in networks with optimal patterns is hydraulically appropriate, meeting hydrodynamic pressure conditions suggested in water supply design standards. Additionally, this study demonstrates a 9% reduction in network energy costs compared to existing patterns. The model presented herein offers a means to efficiently operate water supply systems through water tanks, thereby reducing energy costs.