31 / 2021-10-03 13:25:22

Research on SMES Smoothing Wind Power Based on Fuzzy EEMD Decomposition

Wind power fluctuations, Ensemble Empirical Mode Decomposition (EEMD), State of Charge (SOC), Superconducting Magnetic Energy Storage (SMES)

Power system and automation > Modeling, control and stability analysis in power system

This paper proposes an energy storage smoothing wind power fluctuation control scheme based on wind speed prediction. The predicted output power is used to replace the historical output data for analysis. In order to solve the shortcomings of traditional filtering algorithms, Ensemble Empirical Mode Decomposition (EEMD) was adopted to implement adaptive smoothing for fluctuating wind power, and the selection method of EEMD smoothing base order was designed based on the continuous mean square error criterion and the wind farm grid-connected power change constraint standard. Comprehensively considering the State of Charge (SOC) and fluctuation index of the energy storage device, a fuzzy variable-order control strategy of Superconducting Magnetic Energy Storage (SMES) smoothing wind power is designed. While ensuring that the fluctuation of wind power reaches the standard, SMES is in good working condition. Using the actual power data of a wind farm, the simulation comparison with the fixed-order smoothing method verifies the effectiveness of the fuzzy EEMD smoothing method and improves the real-time performance of the control system. This scheme can not only reduce the impact of fluctuating power on the grid and improve the reliability of wind power grid-connected operation, but also meet the needs of grid dispatching, which has certain guiding significance for practical engineering applications.