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Wavelet Transform for Processing Power Quality Disturbances

EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 047695 (2007) Cite this article

Abstract

The emergence of power quality as a topical issue in power systems in the 1990s largely coincides with the huge advancements achieved in the computing technology and information theory. This unsurprisingly has spurred the development of more sophisticated instruments for measuring power quality disturbances and the use of new methods in processing and analyzing the measurements. Fourier theory was the core of many traditional techniques and it is still widely used today. However, it is increasingly being replaced by newer approaches notably wavelet transform and especially in the post-event processing of the time-varying phenomena. This paper reviews the use of wavelet transform approach in processing power quality data. The strengths, limitations, and challenges in employing the methods are discussed with consideration of the needs and expectations when analyzing power quality disturbances. Several examples are given and discussions are made on the various design issues and considerations, which would be useful to those contemplating adopting wavelet transform in power quality applications. A new approach of combining wavelet transform and rank correlation is introduced as an alternative method for identifying capacitor-switching transients.

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  1. School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore

    S. Chen & H. Y. Zhu

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  1. S. Chen
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  2. H. Y. Zhu
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Correspondence to S. Chen.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Chen, S., Zhu, H.Y. Wavelet Transform for Processing Power Quality Disturbances. EURASIP J. Adv. Signal Process. 2007, 047695 (2007). https://doi.org/10.1155/2007/47695

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