An Applicability of Teager Energy Operator and Energy Separation Algorithm for Waveform Distortion Analysis : Harmonics, Inter-harmonics and Frequency Variation

Abstract

-This paper deals with an application of Teager Energy Operator (TEO) and Energy Separation Algorithm(ESA) to detect and determine various voltage waveform distortions like harmonics, inter-harmonics and frequency variation. Because the TEO and DESA algorithm was initially proposed for speech or communication analysis, its applications are limited to some types of waveform in the power quality analysis area. For example, an undistorted voltage signal is similar with a pure sinusoid. A voltage fluctuation is very similar with an amplitude-modulated signal, from the viewpoint of signal theory. And a continuous frequency variation is similar with a frequencymodulated signal, which is also known as a chirp signal. This paper is written to show that the TEO and DESA algorithm can be used for detecting occurrences of the representative waveform distortions and determining their instantaneous information of amplitude and frequency.

Overview of Signal Processing and Machine Learning for Smart Grid Condition Monitoring

“…The main disadvantage of this operator is its sensitivity to noise and model mismatch. Moreover, it assumes that the estimated IF does not vary too fast or too greatly compared to the nominal frequency [141,142].…”

Advanced Railway Power Quality Detecting Algorithm Using a Combined TEO and STFT Method

“…This inherent characteristic makes it used in many applications about PQ monitoring, especially, transient phenomenon and voltage fluctuation or flicker [5]~ [7]. Unlike the previous papers, the reference [4] deals with an applicability of TEO and discrete energy separation algorithm(DESA) for waveform distortions like harmonics, inter-harmonics and frequency variation. However, most of them are focusing on the detection and the data extraction by DESA, leading to a result that the simple TEO method has an excellent performance to detect the starting and ending instances of an event.…”

“…1 and 2 show the TEO analysis results of 10%, 4-cycle voltage sag signal without and with a small noise. Additionally, the magnitude and frequency components are restored by DESA(Discrete Energy Separation Algorithm) as referred to the reference [4].…”

“…However, the existing PQ monitoring system is not enough to the noise-sensitive interruptions such as sag, harmonics and inter-harmonics contaminated by small noises. Reference [4] introduces the fast fault detection technique, TEO and DESA algorithms, which have been proven to have a good and fast performance for event detection. This paper is written and organized to examine the weakness of TEO and to introduce an advanced detecting and analyzing technique, Combined TEO(Teager Energy Operator) and STFT(Short-time Fourier Transform) algorithm.…”