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Abstract In microgrids, energy storage systems (ESS) can mitigate the intermittency and uncertainty associated with large amounts of renewable energy connected to the grid. Cloud energy storage (CES) is a solution proposed by scholars over the last two years. It provides energy storage and trading services that can alleviate high investment costs and small‐scale wind and light abandonment problems. However, large‐scale energy mutualisation and fine scheduling of energy become significant challenges for further development. This study proposes a CES scheduling architecture based on multi‐microgrids. CES extends the scope of power trading from a single microgrid to multi‐microgrids, with the microgrid capable of interacting with neighbouring microgrids for power and reducing the transmission pressure on the larger grid. In addition, this study defines the game strategy for power trading between cloud storage operators, considering the reduction in electricity costs due to dishonest behaviour by users. The simulation results indicate that the proposed dispatching architecture and strategy can effectively improve the consumption rate of new energy sources, mitigate grid fluctuations, and further reduce electricity costs for users while also being resilient to dishonest user behaviour.

Abstract In wind farms, the energy storage system can realize the time and space transfer of energy, alleviate the intermittency of renewable energy and enhance the flexibility of the system. However, the high cost limits its large‐scale application. Cloud energy storage (CES) can provide users with leasing energy storage service at a relatively lower price, and can provide energy trading service. Wind farms can lease CES and participate in energy transaction to reduce the cost of energy storage and suppress wind power fluctuations. This paper proposes a framework of wind farm system based on CES service, and designs a power allocation strategy. Considering whole‐life‐cycle cost of the self‐built energy storage, leasing and trading cost of the CES and penalty cost of wind abandonment and smooth power shortage, an optimal configuration model of combined energy storage capacity in wind farms based on CES service was established to minimize the total annual cost. Taking a wind farm in Germany as a case study, it is verified that the model in this paper can effectively reduce the cost, extend the service life of self‐built energy storage equipment and suppress the wind power fluctuations.