A Double-layer Robust Optimization Model for Energy Storage Capacity Allocation in the Leasing Market

Multiple application scenarios and rich business models are effective ways to scale the layout of shared energy storage, which is conducive to improving the economic benefits of shared energy storage and can also supplement the regulatory resources of the power grid. Based on the autonomy and convenience of shared energy storage, a robust two-layer optimization method for shared energy storage configuration that considers cluster leasing of wind farms in the market environment is proposed. This paper describes the commercial operation model of shared energy storage to provide leasing services and participate in spot market transactions. Considering the uncertainty of wind turbine output and spot price on multiple time scales, a master-slave game robust optimization model of shared energy storage configuration is constructed. The upper layer of the model aims to minimize the annual cost of shared energy storage. It determines the lease price and capacity planning scheme of each period of shared energy storage under the scenario of an interactive game of wind farm clusters. The lower layer of the model aims at the lowest assessment cost of the wind farm cluster. It uses the lease price of each period and the leasing demand under the worst scenario of the output power of the wind turbine to update the lease capacity of each period. The validity of the configuration results is verified through multi-scenario comparative analysis, which provides a new idea for the capacity optimization configuration of multi-application scenarios with shared energy storage.