Electric power quality disturbance classification using self-adapting artificial neural networks

Janaka V. Wijayakulasooriya; Ghanim Putrus; Peter Minns

doi:10.1049/ip-gtd:20020014

Electric power quality disturbance classification using self-adapting artificial neural networks

Janaka V. Wijayakulasooriya, Ghanim Putrus, Peter Minns

Mathematics, Physics and Electrical Engineering

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

54 Citations (Scopus)

8 Downloads (Pure)

Original language	English
Pages (from-to)	98
Journal	IEE Proceedings: Generation, Transmission and Distribution
Volume	149
Issue number	1
DOIs	https://doi.org/10.1049/ip-gtd:20020014
Publication status	Published - Jan 2002

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10.1049/ip-gtd:20020014

Electric power quality disturbance classification using self-adapting artificial neural networksAccepted author manuscript, 188 KB

Cite this

@article{62313e21775d462b8a84ffd5fe745c88,

title = "Electric power quality disturbance classification using self-adapting artificial neural networks",

keywords = "computer simulation, discrete wavelet transform, fast Fourier transform, feature vectors",

author = "Wijayakulasooriya, {Janaka V.} and Ghanim Putrus and Peter Minns",

note = "This work on the “Power Quality” which is now recognised an essential feature that largely affects the performance of modern power networks. This paper presents a new technique for classifying electrical power quality disturbance events based on a novel Self-Adapting Artificial Neural Network (SAANN), which has the unique capability of adapting to new disturbances. A PhD project (J. V. Wijayakulasooriya) funded by the University studentship.",

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AU - Wijayakulasooriya, Janaka V.

AU - Putrus, Ghanim

AU - Minns, Peter

N1 - This work on the “Power Quality” which is now recognised an essential feature that largely affects the performance of modern power networks. This paper presents a new technique for classifying electrical power quality disturbance events based on a novel Self-Adapting Artificial Neural Network (SAANN), which has the unique capability of adapting to new disturbances. A PhD project (J. V. Wijayakulasooriya) funded by the University studentship.

PY - 2002/1

Y1 - 2002/1

KW - computer simulation

KW - discrete wavelet transform

KW - fast Fourier transform

KW - feature vectors

U2 - 10.1049/ip-gtd:20020014

DO - 10.1049/ip-gtd:20020014

M3 - Article

VL - 149

SP - 98

JO - IET Generation, Transmission and Distribution

JF - IET Generation, Transmission and Distribution

SN - 1751-8687

IS - 1

ER -