ROCOF Estimation via EMD, MEMD and NA-MEMD
This paper presents results of the rate of change of frequency (ROCOF) estimation using Huang’s Empirical Mode Decomposition (EMD), Multivariate Empirical Mode Decomposition (MEMD) and Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD). On the generated test signals algorithms are performed and the obtained results are compared and discussed. The results are compared with actual values of the rate of change of frequency obtained by derivatization of the generated test signals as input data of the aforementioned algorithms. The performance of the algorithm are also tested using signals contaminated by zero-mean Gaussian noise. The results of rate of change of frequency estimation indicates that all three algorithms have great accuracy in the rate of change of frequency estimation.
- 2.Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.-C., Tung, C.C., Liu, H.H.: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. R. Soc. London A 454(1971), 903–995 (1998)Google Scholar
- 4.Hou, T.Y., Shi, Z.: Data driven time frequency analysis. Appl. Comput. Harmon. Anal. 35(2), 284–308 (2013)Google Scholar
- 11.Rehman, N.U., Park, C., Huang, N.E., Mandic, D.P.: EMD via MEMD: multivariate noise aided computation of standard EMD. Adv. Adapt. Data Anal. 5(2), 1350007 (2013)Google Scholar
- 13.Dedović, M.M., Avdaković, S.: A new approach for df/dt and active power imbalance in power system estimation using Huang’s empirical mode decomposition. Int. J. Electr. Power Energ. Syst. 110, 62–71Google Scholar