Energy-efficient optimal operation of water supply pump stations based on an improved multi-objective particle swarm optimization algorithm

The operation of pumps incurs significant operational costs in water supply systems. To address the issues of high energy consumption and frequent pump start-stop cycles in traditional water supply pump stations, this study proposes an energy-saving optimal scheduling strategy based on an improved adaptive weight-based multi-objective particle swarm optimization algorithm (AW-MOPSO). Establish a dual-objective optimization model that aims to minimize electricity consumption and maintenance costs. By integrating variable frequency speed control technology for pumps, the (AW-MOPSO) algorithm is employed to solve for the Pareto front set of the optimization problem. Experimental results demonstrate that the proposed method effectively reduces energy consumption and minimizes equipment wear, while ensuring water supply requirements are met and maintaining stable operation of the pump units during regulation. These outcomes validate the feasibility and superiority of the proposed approach.