Mid-Term Optimal Scheduling of Hydro-Wind-Solar Systems Addressing Extreme Drought and Renewable Energy Forecast

With the acceleration of global energy transition and frequent extreme drought events, the combined threat of low output in renewable energy forecast and sudden reductions in hydropower generation poses significant challenges to power grid security and stability. This paper proposed a flexibility regulation capability assessment method for hydropower systems to address low output in mid-term extreme forecast errors of renewable energy under extreme drought conditions. First, the auto-regressive moving average model (ARMA), standardized runoff index (SRI), and run theory were employed to construct inflow scenarios under extreme drought conditions. Subsequently, based on kernel density estimation and Copula theory, the scenario of wind-solar systems under extreme forecast error was established. On this basis, a mid-term complementary scheduling model for hydro-wind-solar systems was developed with the objective of minimizing total operational costs. The original model was transformed into a mixed-integer linear programming (MILP) model through the linearization of both objective functions and constraints. Case studies on a hydro-wind-solar integrated base of a basin in Southwest China demonstrated that the proposed method could quantitatively evaluate the flexibility regulation capacity of cascade hydropower systems in addressing low output in mid-term extreme forecast errors of renewable energy under extreme drought conditions. The paper further proposed operational strategies including critical water level control and tolerance coefficient for hydropower energy storage loss, providing theoretical support for ensuring secure and stable operation of hydro-wind-solar integrated bases under extreme conditions.