What is it about?
PQ disturbances affect the power systems in terms of economy and reliability. To address this issue it is necessary to predict the disturbances in a fast and efficient manner. This paper presents a new technique for the same.
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Why is it important?
Presence of noise is a critical issue in PQ disturbance classification problems. This paper presents a new technique which has a highly noise tolerant architecture and leads to better accuracy in prediction of disturbances
Perspectives
Three significant contributions have been to power quality analysis through this paper: 1) Introducing a new technique to PQ analysis, i.e. Fractional Fourier Transform 2) Highly noise immune classification scheme 3) Introduction of a new classifier, i.e. Bagging predictors
Mr. Utkarsh Singh
Indian Institute of Technology Roorkee
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This page is a summary of: Application of fractional Fourier transform for classification of power quality disturbances, IET Science Measurement & Technology, January 2017, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-smt.2016.0194.
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