Wavelet based detection of power quality disturbance - A case study

Christy, J. Ida; Vedamani, X. Jeno; Karthikeyan, S.

doi:10.1109/icsccn.2011.6024534

Cited by 10 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Considering that, the energy is the quadratic sum for each component of each detail leaf decomposed, the percentage energy can be obtained by Equation 1.…”

Section: Methodsmentioning

confidence: 99%

“…In general, Wavelet Transforms (WT) has been used for many years in such areas as image compression, mechanical vibrations and acoustic analysis [1]. Many studies on the use of WT in signal analysis have shown their ability to filter noise and for accurate detection of abrupt changes and discontinuities in electrical signals, as well as feature extraction [5].…”

Section: Introductionmentioning

confidence: 99%

“…Any frequency variations or voltage waveform distortions can result in misoperation and/or failures of consumer's equipment, which can reduce their lifetime [1], [2].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, to ensure a better PQ of a distribution power system, methods for automatic detection, classification, location and data storage became essential [1], [5]. In this sense, continuous data recording (with or without disturbances) are required, which leads to a huge volume of data to be inspected by experts [2], [3].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Adaptive Threshold for Electrical Disturbances Segmentation

Andrade

Oleskovicz

Fernandes

et al. 2014

REPQJ

View full text Add to dashboard Cite

Abstract. The detection of the electrical signal discontinuities in the oscillographies recorded in substations and/or points of common coupling allows their segmentation, which is crucial for implementation of automated methods for detection, classification, location and storage by classes of disturbances in electric power systems. In this context, this study provides a way of determining an adaptive threshold that allows the segmentation of voltage or current signals based on Wavelets decomposition. The disturbances considered in this work were the short-duration voltage variations, impulsive and oscillatory transients, and harmonic distortions. The signals were synthetically generated. Moreover, white noise was added on the signals. Thus, a Symlet Wavelet was applied to the signals in order to denoise them. In the sequence, a Daubechies Wavelet was used to decompose the filtered signals. So, to determine the initial and final points of each segment, an adaptive threshold was established based on the energy and entropy of energy for the second level of decomposition. Thus, the number and position of each segment were determined according to the intersections of the detail curves and the thresholds found.

show abstract

“…Considering that, the energy is the quadratic sum for each component of each detail leaf decomposed, the percentage energy can be obtained by Equation 1.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Any frequency variations or voltage waveform distortions can result in misoperation and/or failures of consumer's equipment, which can reduce their lifetime [1], [2].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Threshold for Electrical Disturbances Segmentation

Andrade

Oleskovicz

Fernandes

et al. 2014

REPQJ

View full text Add to dashboard Cite

show abstract

“…The application of entropy in the power systems was started because the system under investigation will have different entropy values under different states. In [46][47][48][49][50][51][52][53][54], various methods for power system state estimation, fault detection, and power quality disturbance detection have been presented. It is also seen from these papers that the main objective is the detection and classification of power systems events by using the entropy approach.…”

Section: Introductionmentioning

confidence: 99%

Wavelet entropy and its application for flicker contribution evaluation

Silsüpür

Türkay

2018

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

As a result of the integration of various new load types and generation units into electric power systems, power quality disturbances such as sag–swell, harmonics, inter‐harmonics, and flicker have come into focus in the last decades. Among these disturbances, flicker is one of the serious power quality issues for both power system operators and users. In addition to having direct effects on human life such as the discomfort caused by visual disturbance, flicker may cause incorrect operations of electrical devices. Furthermore, finding a dominant flicker source in order to mitigate it and supply high‐quality power to users are the main tasks of network operators. The measurement of the flicker level is defined in the IEC 61000‐4‐15 standard as measured by a flicker meter; however, it deals only with voltage signals and is not sufficient to understand the contribution of the load and background power systems separately. Therefore, this paper proposes new approaches to the evaluation of flicker characteristics using simulated and real signals. The novelty of this paper is that it investigates the flicker characteristics in the light of multi‐resolution wavelet analysis and information‐theory‐based wavelet energy entropy analysis together and proposes a new index to interpret flickers' responsibility in load and flicker source detection. The proposed method uses only voltage and current signals and does not require additional calculation of any network parameter such as the system impedance. The proposed method is validated by simulations as well as site measurements, and the results show the accuracy and suitability of the proposed method. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

show abstract