An Optimization Method for Day-Ahead Generation Interval of Cascade Hydropower Adapting to Multi-Source Coordinated Scheduling Requirements

Multi-source coordinated scheduling has become the predominant operational paradigm in power systems. However, substantial differences among hydropower, thermal power, wind power, and photovoltaic sources in terms of response speed, regulation capability, and operational constraints—particularly the complex generation characteristics and spatiotemporal hydraulic coupling of large-scale cascade hydropower stations—significantly increase the complexity of coordinated scheduling. Therefore, this study proposes an optimization method for determining the day-ahead generation intervals of cascade hydropower, applicable to multi-source coordinated scheduling scenarios. The method fully accounts for the operational characteristics of hydropower and the requirements of coordinated scheduling. By incorporating stochastic operational processes, such as reservoir levels and power outputs, feasible boundaries are constructed to represent the inherent uncertainties in hydropower operations. A stochastic optimization model is then formulated to determine the generation intervals. To enhance computational tractability and solution accuracy, a linearization technique for stochastic constraints based on duality theory is introduced, enabling efficient and reliable identification of hydropower generation capability intervals under varying system conditions. In practical applications, other energy sources can develop their generation schedules based on the feasible generation intervals provided by hydropower, thereby effectively reducing the complexity of multi-source coordination and fully leveraging the regulation potential of hydropower. Multi-scenario simulations conducted on six downstream cascade reservoirs in a river basin in Southwest China demonstrate that the proposed method significantly enhances system adaptability and scheduling efficiency. The method exhibits strong engineering applicability and provides robust support for multi-source coordinated operation.