Research on Optimal Scheduling of Water Supply System Based on GA-PSO Algorithm

This study proposes a genetic particle swarm hybrid optimization algorithm (GA-PSO), and uses it to optimize the scheduling of a water supply system of a water treatment plant that only contains fixed-frequency pumps, so as to reduce the frequent start-stop of fixed-frequency pumps and save system operating costs. First, the composition and cost type of the water supply system are introduced, the system scheduling model is constructed, and the constraints and optimization objectives are determined; secondly, the GA-PSO is proposed, the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm are connected in series to solve the problem that the single optimization algorithm converges slowly and is prone to fall into the local optimal solution; finally, the results of the GA-PSO were compared with the GA and PSO under the same problem conditions. GA-PSO is used to optimize the scheduling of each module of the system, and the optimization scheduling results are compared with the historical scheduling data. The optimization method has been proven to be effective, which can reduce the number of starts and stops of fixed-frequency pumps while saving about 6.74% of operating costs.