Optimization Scheduling of Cascade Pumping Stations Based on Improved Northern Goshawk Algorithm

To address the issues of low efficiency and high energy consumption in cascade pump stations systems, this study developed an optimization scheduling model and solved it using the Northern Goshawk Optimization (NGO). NGO features a fast convergence rate and high optimization accuracy. However, NGO is prone to falling into local optima during the solving process. To overcome this issue, the Subtraction-Average-Based Optimizer and Cauchy mutation are combined to propose an Improved Northern Goshawk Optimization (INGO). Experimental tests using benchmark functions showed that the INGO demonstrated significant advantages in optimization performance. INGO was applied to the optimization scheduling of the three-level pump stations in Shanxi Province’s Wanjiazhai Yellow River Diversion Project, verifying its feasibility and effectiveness for solving cascade pump stations scheduling problems. The results showed that, compared to existing schemes, the INGO-based optimization scheme improved the efficiency of cascade pump stations operation by $1.09 \%-1.43 \%$, surpassing the efficiency achieved by NGO.