Abstract:

The construction of large-scale renewable energy bases has promoted the low-carbon transformation of the power system, with renewable energy stations and energy storage playing an increasingly important role in power dispatch and market transactions. At the same time, the sharing economy model has gained favor among scholars for its ability to improve the utilization of idle resources. This paper investigates the joint optimization operation mode of clustered renewable energy stations and shared energy storage in renewable energy bases. First, a joint optimization operation framework for clustered renewable energy stations and shared energy storage in renewable energy bases is established. Then, a two-stage optimization model for renewable energy stations and shared energy storage, considering green power trading, is developed. To address the uncertainty of renewable energy generation, an uncertainty set that accounts for the temporal characteristics of wind and solar power errors is constructed, which can reflect the true fluctuation range of renewable energy output. On this basis, a day-ahead and intraday two-stage robust model is built. Finally, the idle capacity of shared energy storage is utilized to participate in both the energy and reserve markets, improving energy storage utilization and expanding its profit channels. Case studies verify the effectiveness of the proposed model and method. The results show that the proposed optimization operation strategy can significantly reduce the penalty cost for renewable energy station deviations, accelerate the recovery of energy storage investment, and ultimately increase the net profit of the renewable energy base.

Key words: clustered renewable energy stations, shared energy storage, green power market, two-stage robust optimization