Wind Power Smoothing with Genetic Algorithm Based Fuzzy Control of Energy Storage in Wind Farm

To achieve the smoothing and grid connection of wind power, an energy storage system is used to mitigate wind power fluctuations. Firstly, based on the adaptive improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), wind power is adaptively decomposed and reconstructed to obtain the power instructions for wind power grid connection and energy storage charge and discharge. Secondly, according to the output requirements of the energy storage system and considering the state of charge (SOC) of the energy storage, a fuzzy control method is employed to adjust the power instructions for the energy storage, obtaining optimized power instructions. Finally, genetic algorithms are utilized to optimize the fuzzy membership parameters, reducing the impact on grid-connected power while optimizing the SOC. Case studies demonstrate that the proposed control strategy can achieve the smoothing and grid connection of wind power, ensuring that the energy storage SOC operates within a reasonable range.