Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN

This paper presents the study of voltage and power stability margins of an electrical power system with the use of artificial neural network (ANN).Both voltage and power stability margins are obtained from the real power-voltage (PV) and reactive power-voltage (QV) curve.PV and QV curve are generat...

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Main Author: Marizan, Sulaiman
Format: Article
Language:English
Published: IET 2016
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/20819/2/marizan_78.pdf
http://eprints.utem.edu.my/id/eprint/20819/
https://ieeexplore.ieee.org/document/8278596/?denied
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spelling my.utem.eprints.208192021-07-08T21:02:13Z http://eprints.utem.edu.my/id/eprint/20819/ Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN Marizan, Sulaiman T Technology (General) TK Electrical engineering. Electronics Nuclear engineering This paper presents the study of voltage and power stability margins of an electrical power system with the use of artificial neural network (ANN).Both voltage and power stability margins are obtained from the real power-voltage (PV) and reactive power-voltage (QV) curve.PV and QV curve are generated by a series of power flow with an incremental of loads for each power flow series.Then,an ANN based model will be used to predict the values of voltage and power stability margins.IEEE 30-bus system has been chosen as the electrical power system.The load flow analysis are simulated by using Power World Simulator software version 16.The ANN based model is developed using MATLAB. IET 2016-11 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/20819/2/marizan_78.pdf Marizan, Sulaiman (2016) Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN. IET Digital Library / Conference, 1 (1). pp. 1-7. ISSN - https://ieeexplore.ieee.org/document/8278596/?denied
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Marizan, Sulaiman
Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN
description This paper presents the study of voltage and power stability margins of an electrical power system with the use of artificial neural network (ANN).Both voltage and power stability margins are obtained from the real power-voltage (PV) and reactive power-voltage (QV) curve.PV and QV curve are generated by a series of power flow with an incremental of loads for each power flow series.Then,an ANN based model will be used to predict the values of voltage and power stability margins.IEEE 30-bus system has been chosen as the electrical power system.The load flow analysis are simulated by using Power World Simulator software version 16.The ANN based model is developed using MATLAB.
format Article
author Marizan, Sulaiman
author_facet Marizan, Sulaiman
author_sort Marizan, Sulaiman
title Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN
title_short Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN
title_full Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN
title_fullStr Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN
title_full_unstemmed Study Of Voltage And Power Stability Margins Of Electrical Power System Using ANN
title_sort study of voltage and power stability margins of electrical power system using ann
publisher IET
publishDate 2016
url http://eprints.utem.edu.my/id/eprint/20819/2/marizan_78.pdf
http://eprints.utem.edu.my/id/eprint/20819/
https://ieeexplore.ieee.org/document/8278596/?denied
_version_ 1705060035840704512
score 13.159267