A novel method for analyzing dominant oscillation mode based on improved EMD and signal energy algorithm

Abstract

In this paper, a novel method that integrates the improved empirical mode decomposition (EMD) and signal energy algorithm is proposed to estimate the dominant oscillation parameters and corresponding mode shape. Firstly, the EMD with symmetrical extrema extension (SEE) is utilized to decompose the measured data from wide area measurement system (WAMS) into a finite set of intrinsic mode functions (IMFs). Then, the signal energy algorithm is used to calculate the approximate oscillation parameters of the IMFs. The nodes involved the dominant oscillation mode are classified based on the calculated frequency and reasonable threshold. Furthermore, for the dominant oscillation mode, the IMF with maximum mean amplitude is defined as the reference. Next, the relative phases (RPs) between the reference IMF and other IMFs are calculated in order to identify the negative and positive oscillation groups. According to the values of RPs, the coherent group and corresponding node contribution factor (NCF) can be identified, and the dominant approximate mode shape (AMS) can also be determined. The efficiency of the proposed approach is tested by applying it to synthetic signal and measured data from the simulation model. low frequency oscillation, wide area measurement system, symmetrical extrema extension, signal energy algorithm, total oscillation energy, node oscillation energy, node contribution factor Citation:Yang D C, Rehtanz C, Li Y, et al. A novel method for analyzing dominant oscillation mode based on improved EMD and signal energy algorithm.

An Augmented Prony Method for Power System Oscillation Analysis Using Synchrophasor Data

“…Moreover, the HHT method can determine the contribution of a state variable in a mode based on energy and phase relationship of IMFs. Nevertheless, as stated in the introduction, the HHT method suffers from the EEs, mode-mixing and Gibbs phenomena [6,9]. In this paper, an improved Prony method is proposed that is able to calculate IMFs and thus NCFs for a given signal.…”

“…It is important to emphasize that so far, the Prony method has not been augmented for calculation of IMFs and thus NCFs. Our proposed formulation in this subsection bypasses the problems of nonlinear and the iterative method of HHT method for IMF calculation, such as the mode mixing of EMD, end effect and Gibbs phenomena [6][7][8][9].…”

“…Recently, several studies have attempted to extract oscillation parameters using synchrophasor data. Some of the well-known methods used for oscillation detection using measurement-based approaches include: Kalman Filter (KF) [4] estimation of signal parameters by rotational invariance technique (ESPRIT) [5], Hilbert-Huang transform (HHT) [6][7][8][9], Yule-Walker algorithm [10], wavelet transform (WT) [11], recursive adaptive stochastic subspace identification (RASSI) [12], maximum likelihood method [13], and Prony analysis method [14][15][16]. Among them, the Prony method is one of the most commonly used measurement-based methods.…”

“…However, EMD process has some inherent shortcomings such as the end effects (EEs), mode-mixing and Gibbs phenomena. Some of those drawbacks have been addressed in improved versions of the HHT method in [6][7][8][9].…”

Research focuses and advance technologies of smart grid in recent years

“…Analysis reveals that the AC voltage control of VSC has little impact on the damping of power system oscillations, while the DC voltage control of VSC shows different damping characteristics under different load conditions. A novel approach integrated with the improved empirical mode decomposition and signal energy algorithm was presented to investigate the dominant oscillation mode [41]. In this work, the low frequency oscillation problem was analyzed from the energy view.…”