Multi-Timescale Scheduling Optimization of Cascade Hydro-Solar Complementary Power Stations Considering Spatio-Temporal Correlation

Abstract

The water-PV hybrid generation system is an effective approach to promoting renewable energy integration; however, most existing hydropower stations are run-of-river type with limited annual regulation capacity. Enhancing the PV absorption capacity of such run-of-river hydropower is thus crucial for achieving localized renewable energy utilization. This study proposes a multi-timescale optimization scheduling method for cascade water-PV complementary systems, accounting for spatiotemporal correlations. First, using historical data and Frank-Copula based correlation analysis, we identify the spatiotemporal interactions between water and PV outputs to generate numerous scenarios that capture the coupled characteristics of water-PV generation within the watershed. Considering constraints related to reservoir capacity, water level, flow rate, and individual unit output, a multi-timescale optimization scheduling model is formulated with a single unit as the smallest dispatch unit. To improve computational efficiency, a triangular weighting method is introduced to simplify complex constraints. Finally, a case study within a watershed in Southwest China validates the model's effectiveness and reliability, providing a valuable reference for enhancing PV absorption capacity through the utilization of run-of-river cascade hydropower.