Application of adaptive EEMD method in voltage sag detection

Abstract

In the traditional Ensemble Empirical Mode Decomposition (EEMD) method, the two critical parameters (the amplitude of the added white noise and the number of ensemble trials) are required to be obtained artificially and the added-noise process is non-adaptive. Aiming at the shortcomings of EEMD method, a modified Ensemble Empirical Mode Decomposition (MEEMD) method was proposed. In the proposed method, the added-noise principle of noise assisted decomposition methods were analyzed, and the two parameters: signal-to-noise ratio and correlation coefficient were taken as an evaluation index of decomposition performance, which adaptively determined the optimal amplitude of additive white-noise and number of ensemble trials by calculating the SNR values under different noises and the correlation between obtained components and original components. Furthermore, simulation results show that the proposed method is able to effectively suppress mode mixing and endpoint effects. At last, experiments data measured from the built power quality disturbance platform demonstrate that the proposed method is capable to accurately extract all disturbance parameters of voltage sag, which provides a novel way for power quality disturbance analysis as well.