Economic Configuration of Flywheel Collaborative Battery Hybrid Energy Storage System for Smoothing Wind Power Fluctuations

In response to the fluctuation of active power in wind farms, a power smoothing algorithm based on wavelet packet decomposition was adopted to obtain low-frequency signal components that meet grid connection requirements and high-frequency hybrid energy storage system reference power. Low pass filtering, frequency division and signal smoothing denoising methods were used to obtain reference signals for flywheel energy storage and battery energy storage. Simultaneously, considering the impact of discharge depth and cycle count on the lifespan of the battery energy storage system, a hybrid energy storage system's full life cycle economy model was constructed within the planned years. The optimal configuration of the hybrid energy storage capacity was obtained through multi-tracker optimization algorithm (MTOA). Finally, based on actual power data from the wind farm, simulation analysis was conducted to verify the effectiveness and economic of hybrid energy storage system (HESS) in power smoothing. Results show that HESS can not only ensure that the active power fluctuation of the wind farm meets the grid connection requirements, but also fully utilize the characteristics of different energy storage forms to reduce the operating costs of the system.