ABSTRACT With the increasing penetration of photovoltaic generation and the deep coupling of electricity and heat networks, regional integrated energy systems (RIES) are facing growing operational risks caused by multiple concurrent uncertainties, including renewable generation fluctuations, electro‐thermal conversion efficiency variations, and typical N − 1 contingency events. Conventional deterministic or single‐uncertainty planning methods are insufficient to simultaneously guarantee economic efficiency, operational robustness and system resilience. This paper proposes a bilevel optimization model for energy storage configuration and coordinated operation. Information gap decision theory is used for multi‐uncertainty robust optimization, with heterogeneous uncertainties unified by an L1‐norm set. The resulting bilevel robust optimization problem is reformulated into a single‐level mixed‐integer linear programming model using Karush–Kuhn–Tucker conditions and Big‐M linearization, enabling efficient solution. Case studies based on the modified IEEE‐33 node system demonstrate that the proposed method can effectively coordinate energy storage configuration and operational strategies under multi‐source uncertainty. Compared with conventional robust optimization methods, the proposed framework significantly improves photovoltaic utilization, reduces total operating cost and enhances system robustness and resilience against fault disturbances and efficiency degradation.
Zheng et al. (Thu,) studied this question.