A Wind Power Smoothing Method Based on EMD Concerning Electricity Constraints

The application of energy storage in the smoothing of wind power is one of the latest research hotspots, but there is insufficient research on the problem of frequent energy storage system (ESS) overruns, which will lead to less than ideal results in practical applications. Based on this, this paper proposes a smoothing strategy for wind power based on Empirical Modal Decomposition (EMD) algorithm concerning electricity constraints. On the basis of EMD, the electricity constraint is introduced to solve the problem of energy storage frequently crossing the limit when dissipating. First, according to the EMD algorithm, the wind power signal is decomposed into individual Intrinsic Mode Function (IMF) signals from high frequency to low frequency by considering the operating characteristics of individual energy storage elements in the energy storage system. Then, based on this, the corresponding electricity constraint is set and the original IMF is adjusted from high frequency to low frequency in order to satisfy this power constraint. Finally, simulations of the improved algorithm and the original algorithm are carried out to verify the effectiveness of the proposed algorithm, showing that the smoothing of wind power based on the proposed method can effectively mitigate the impact of wind power fluctuations on the power system and improve the efficiency of wind power utilization.