Coupled optimization of hydropower and variable renewable energy (VRE) synergistically supported by physically-based stochastic scenarios and multi-load node control

Integrating highly regulated hydropower with variable renewable energy (VRE) like wind and photovoltaic into a Hydro-Wind-PV power system is urgent and realistic needs in the energy sector. However, the long-term optimal operation of such integrated systems remains challenging due to the long-term inflow uncertainty and short-term VRE stochasticity, compounded by the fact that existing stochastic scenario methods often lack clear physical interpretation and practical applicability. To address these issues, this study develops a physically-based stochastic scenario modeling approach for efficient hydropower-VRE coordination, in which scenario probabilities are derived from the actual frequency of weather types. Furthermore, a multi-load point control strategy is implemented within a hierarchical optimization framework that couples long-term and short-term operations, aiming to maximize long-term power generation while minimizing short-term average scheduling deviations. The proposed method can generate operable multi-time-scale hydropower output plans for different inflow frequencies and typical weather conditions, providing practical decision support for dispatchers. Case studies conducted on cascade reservoirs in the lower Jinsha River demonstrate that the proposed method effectively balances long-term power generation benefits and short-term scheduling stability, while maintaining total power output at no less than 97% of the initial optimal solution, the average deviation is reduced by approximately 32.2%. By combining transmission capacity expansion with deliberate power spillage strategies, the overall system performance is further enhanced, particularly during high-inflow periods, achieving a 1.2% increase in total power generation alongside a notable reduction in the average deviation and water spillage rate.