Optimal operation of pumped storage units based on mixed-integer linear programming

The incorporation of new energy sources into the power grid causes significant load fluctuations, creating an urgent need for pumped-storage units to provide peak-shaving and valley-filling services. This study presents an optimization scheduling method based on mixed-integer linear programming (MILP) for peak-shaving and valley-filling operations of pumped-storage units. The objectives are to minimize equivalent load variability and maximize power generation benefits. This study linearized the complex multi-dimensional nonlinear constraints of pumped-storage units and utilizes MILP to optimize their operation. A pumped storage power station in Hunan Province, Central China, as a case study, was simulated using typical equivalent load scenarios at 2023. The results showed that, compared with conventional scheduling schemes, the optimized scheme reduced equivalent load variability by more than 5% in four typical scenarios, with a maximum reduction of 34%. Daily power generation benefits reached over 302 000 yuan, with a maximum of 405 000 yuan, demonstrating significant comprehensive benefits. Refined modeling of unit start/stop conditions and hydraulic characteristics limits the number of start/stop cycles for each unit to no more than six, ensuring economical and efficient unit operation. These findings provide technical support for the optimal operation of pumped-storage power systems.