User‐side cloud energy storage configuration and operation optimization considering time‐of‐use pricing and state‐of‐charge management

Abstract Multiple energy storage systems (ESSs) often face imbalances in charging–discharging operations, as well as the uncertainties of practical scenarios and influencing factors. To address these challenges, this study proposes a user‐side cloud energy storage (CES) model with active participation of the operator. This CES model incorporates adjustable time‐of‐use (TOU) electricity pricing and state‐of‐charge (SOC) management. In the configuration process, the net load scenario generation reduction is performed first. Subsequently, demand response is implemented based on the updated TOU pricing. To address the imbalance of ESSs, an improved multiobjective particle swarm optimization is employed, followed by access verification of the multi‐ESS aggregation. In the dispatch process, a two‐stage interval optimization model is adopted. Specifically, day‐ahead scheduling determines the SOC limit interval, and intra‐day scheduling achieves rolling optimization to determine the exact charging–discharging duration. This ensures that the charging–discharging cycles are controllable, orderly, and efficient. Ultimately, a fair settlement method based on optimal pricing of various fees within the “cloud” is proposed, ensuring sustainable revenue growth for all types of users. A case study demonstrates that the proposed methods can achieve multifaceted value in energy management and enhance the socioeconomics of user‐side ESS projects.