The hydro–wind–photovoltaic–storage hybrid system (HWPSS) is an effective approach to achieve efficient utilization of renewable energy sources (RES). To address the high uncertainty of RES and the coordination challenges of hybrid energy storage systems (HESS), this paper proposes an integrated optimization framework for HWPSS based on the coordinated operation of multi-type HESS. This framework determines the capacity of HESS through a nested configuration layer and, in response to source–load uncertainty, constructs a day-ahead, intra-day, and real-time multi-timescale rolling optimization model for coordinating HESS. This model comprehensively considers the differences in response characteristics and energy density among various energy storage technologies and incorporates a dynamic forecasting mechanism to enhance system robustness. A case study is conducted on a hydro–wind–photovoltaic system in southern China. The results demonstrate that various energy storage technologies exhibit complementarity and synergy in functional positioning and capacity allocation; the proposed multi-timescale rolling optimization model can effectively coordinate the operation of the HESS and fully exploit its regulation potential; compared with rule-based methods, the proposed model increases the system's net profit by 6.35% and reduces residual load fluctuation from 1.104 to 0.1149 MW. The proposed framework significantly improves the operational stability and economic efficiency of the HWPSS, providing a reliable solution for high-penetration renewable energy integration and secure grid operation.
Li et al. (Fri,) studied this question.