With the introduction of China's 'dual carbon' goals

the green electricity economy is rapidly developing

making wind-solar-storage power stations a key model for scaling up new energy. Concurrently

the electricity spot market is undergoing continuous reform

which means that the rational allocation of storage capacity has become crucial to enhancing the economic viability of these stations. On this basis

this paper proposes a method for configuring energy storage that considers the clearing of the electricity spot day-ahead and real-time markets

along with the production simulation process of large-scale wind-solar-storage power stations. First

a dual-layer model for storage allocation and operation across multiple time scales is established

based on long-term production simulation and short-term market clearing. The upper layer addresses the energy storage allocation problem under the market model

while the lower layer deals with the production simulation of the station under the market model. Then

a hierarchical- divisive clustering method is used for multi-scenario allocation. The production simulating of wind-solar-storage power stations is proposed

under the market model

taking into account the collaborative interactions between wind

solar

and storage. Finally

a multi-time temporal coupling framework is established. By transforming the sequential timing into stacked parallel

a method for temporal decoupling of the day-ahead and real-time dual-layer model arising from overlapping multiple time scales is designed. The effectiveness of the proposed method is validated using actual relevant data from the Ulanqab wind-solar-storage power station. The results show that configuring storage with a duration of 3.5 to 4 hours of full-power charging and discharging can effectively ensure the economic benefits of wind-solar-storage power stations in the market model.