Aimed at the problems of low operating efficiency and high energy consumption loss

an optimal scheduling model of cascade pumping stations is developed. This model adopts the sparrow search algorithm (SSA) of strong searching ability and high exploratory accuracy

and compares and selects its two parameters: safety threshold and scout ratio. Then

based on this algorithm

we formulate a new optimal scheduling method for cascade pumping stations

and apply it in the case study of a three-stage pumping station in the Miyun Reservoir regulation and storage project. The results show that under three different flow conditions

compared with the current scheme

the system efficiency of the optimized scheme obtained by the particle swarm optimization (PSO) and Pareto-archived (GA) algorithm are increased by 0.03% - 0.18%

and the annual operating cost is saved by ￥9

700 - ￥69

500. More prominent is the SSA optimized scheme in ameliorating the two indexes mentioned above

which can achieve an efficiency increase of 0.98% - 1.20% and an annual operating cost saving of ￥369

000 - ￥443

900. This verifies the feasibility and efficiency of SSA in the optimal scheduling of cascade pumping stations

along with its application to the scheduling as a reasonable and reliable method.