With the advancement of energy storage technologies and the rapid development of the sharing economy, the shared energy storage (SES) service paradigm has emerged as a novel form of user-side energy storage application. However, complex interest interactions and energy coupling pose challenges to the effective management of microgrid cluster-SES (MGSC-SES) joint systems. To address these challenges, this paper constructs an equilibrium model for the joint system to characterize the interactions among entities. To achieve model equilibrium, an innovative distributed solution algorithm tailored to MGSC-SES is proposed. This algorithm maintains the confidentiality of entities' local operational data (e.g., internal load forecasts and generation plans) while verifying the equivalence between the trading prices set by SES and the optimal solution of the system's dual variables. Additionally, to mitigate inherent uncertainties from renewable energy sources (wind/solar) and market electricity prices, this paper adopts distributionally robust optimization based on the Wasserstein metric—ensuring the model's robustness without excessive conservatism. Finally, the effectiveness and rationality of the proposed model and algorithm are validated through detailed comparative analysis of simulation results across multiple testing scenarios.
Cai et al. (Thu,) studied this question.
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