Multiple Time-scale Medium and Long-term Optimal Scheduling of Cascade Small Hydropower Generation Stations

Cascade small hydropower scheduling enhances clean energy development and reduces fossil fuel dependence, exhibiting strong regulation ability and fast start-up speed. It improves power system flexibility and adapts to electricity market demands. The main goal is to fully utilize regulating capacity, expand capacity, and extend power generation time, ensuring grid safety and stability. However, scheduling faces technical challenges due to the increasing number of cascade reservoirs, randomness of original information, electricity market reforms, and growing hydropower station capacities. To address these, this paper proposes an optimal algorithmic solution for multiple time-scale scheduling of cascade small hydropower stations based on inflow water prediction. Simulation experiments verify the solution’s effectiveness under different operational conditions, contributing to optimal scheduling, improved water resource utilization, and power structure optimization.