Improved nucleolus method-based rolling optimization operation for renewable energy stations and shared energy storage

In the context of renewable energy integration, shared energy storage (SES) offers a promising solution for improving the operational flexibility and economic performance of renewable energy stations (RESs). This paper proposes an improved nucleolus method-based rolling optimization operation method for RESs and SES to address operational uncertainties and ensure fair revenue distribution among RESs. The proposed method comprises a profit maximization model for the cooperative alliance that dynamically adjusts the RESs’ bidding strategies in both day-ahead and real-time energy markets using a receding horizon control approach, as well as an improved nucleolus-based revenue allocation model enhanced with constraint generation techniques to ensure fair, stable and efficient profit sharing among large-scale alliance members. This methodology effectively addresses uncertainties in renewable energy output, market prices and forecast deviations, while maintaining system stability and fairness in cost-sharing. Case study results show that the proposed method improves overall alliance revenue, reduces deviation penalty costs, and significantly decreases computation time, thereby underscoring its scalability and practical feasibility for large-scale RES alliances.