To improve the power quality of wind energy

increase the participation of wind farms in the electricity market

and achieve reasonable energy storage allocation

wind farm energy storage optimization strategy based on information gap decision theory (IGDT) is proposed under the Guangdong electricity market trading rules

considering the uncertainty in electricity energy and frequency regulation ancillary service market prices. In the configuration stage

the configuration incorporates operational considerations and proposes a two-level optimization model for wind farm with integrated energy storage. The upper level optimizes energy storage allocation by maximizing the annual net revenue of the wind-storage system

while the lower level optimizes the system's operation based on actual operating scenarios

aiming to maximize daily operational revenue. To address the price uncertainty in the lower-level model

a price deviation factor is introduced using IGDT. Based on the two-level model

an IGDT-based energy storage optimization configuration model is constructed with the goal of maximizing the price deviation factor. The energy storage configuration is jointly optimized. Simulation results demonstrate that the proposed strategy can achieve economically feasible energy storage configurations under electricity market price fluctuations.