Monitoring HVDC systems using wavelet multi-resolution analysis

A. M. Gaouda; E. F. El-Saadany; M. M.A. Salama; V. K. Sood; A. Y. Chikhani

doi:10.1109/59.962411

Monitoring HVDC systems using wavelet multi-resolution analysis

A. M. Gaouda
, E. F. El-Saadany
, M. M.A. Salama
, V. K. Sood
, A. Y. Chikhani

Electrical Engineering

University of Waterloo
IEEE
Concordia University
Royal Military College of Canada

Research output: Contribution to journal › Article › peer-review

57 Scopus citations

Abstract

The paper presents a disturbance classification technique based on wavelet multi-resolution analysis. The wavelet multi-resolution transform is introduced as a tool for providing discriminative, translation-invariant features with small dimensions to classify different disturbances in an HVDC transmission system. The proposed method extracts features from signals monitored on both DC and AC sides of the HVDC system. It is shown that monitored signals show promising features that can classify different disturbances that may occur anywhere in the HVDC system.

Original language	British English
Pages (from-to)	662-670
Number of pages	9
Journal	IEEE Transactions on Power Systems
Volume	16
Issue number	4
DOIs	https://doi.org/10.1109/59.962411
State	Published - Nov 2001

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Commutation failure
Feature extraction
HVDC system
Multiresolution signal decomposition
Wavelet analysis

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10.1109/59.962411

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title = "Monitoring HVDC systems using wavelet multi-resolution analysis",

abstract = "The paper presents a disturbance classification technique based on wavelet multi-resolution analysis. The wavelet multi-resolution transform is introduced as a tool for providing discriminative, translation-invariant features with small dimensions to classify different disturbances in an HVDC transmission system. The proposed method extracts features from signals monitored on both DC and AC sides of the HVDC system. It is shown that monitored signals show promising features that can classify different disturbances that may occur anywhere in the HVDC system.",

keywords = "Commutation failure, Feature extraction, HVDC system, Multiresolution signal decomposition, Wavelet analysis",

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AU - El-Saadany, E. F.

AU - Salama, M. M.A.

AU - Sood, V. K.

AU - Chikhani, A. Y.

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AB - The paper presents a disturbance classification technique based on wavelet multi-resolution analysis. The wavelet multi-resolution transform is introduced as a tool for providing discriminative, translation-invariant features with small dimensions to classify different disturbances in an HVDC transmission system. The proposed method extracts features from signals monitored on both DC and AC sides of the HVDC system. It is shown that monitored signals show promising features that can classify different disturbances that may occur anywhere in the HVDC system.

KW - Commutation failure

KW - Feature extraction

KW - HVDC system

KW - Multiresolution signal decomposition

KW - Wavelet analysis

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JF - IEEE Transactions on Power Systems

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ER -

Monitoring HVDC systems using wavelet multi-resolution analysis

Abstract

UN SDGs

Keywords

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