Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM)

This paper presents a new hybrid optimisation technique for voltage stability prediction called Artificial Immune Least Square Support Vector Machine (AILSVM). In this paper, a newly developed index named as Voltage Stability Condition Indicator (VSCI) was used to assess the stability condition of l...

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Main Authors: Abaziz N.F., Rahman T.K.A., Zakaria Z.
Other Authors: 57221906825
Format: Conference Paper
Published: IEEE Computer Society 2023
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spelling my.uniten.dspace-221462023-05-16T10:47:49Z Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM) Abaziz N.F. Rahman T.K.A. Zakaria Z. 57221906825 8922419700 56276791800 This paper presents a new hybrid optimisation technique for voltage stability prediction called Artificial Immune Least Square Support Vector Machine (AILSVM). In this paper, a newly developed index named as Voltage Stability Condition Indicator (VSCI) was used to assess the stability condition of load buses in a system. VSCI was derived from a current equation in a complex form of a general 2-bus system. Support Vector Machine (SVM) has been proven to be a powerful tool for solving numerous problems in many fields. However, in order to obtain its best performance, a right combination of SVM parameters is needed. Therefore, Artificial Immune System (AIS) was used as the evolutionary search technique to optimise the value of SVM parameters. The simulations were carried out in a steady state analysis and the data generated were trained and tested under various types of loading conditions either due to an increase in active and/or reactive power. The obtained results show that the proposed methods can successfully give a very good prediction with the predicted values very close to the actual value. All simulations were tested on IEEE 30 bus Reliability Test Systems (RTS). © 2014 IEEE. Final 2023-05-16T02:47:49Z 2023-05-16T02:47:49Z 2014 Conference Paper 10.1109/PEOCO.2014.6814501 2-s2.0-84901339889 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901339889&doi=10.1109%2fPEOCO.2014.6814501&partnerID=40&md5=802f2de41a9f8c2981f687861d100205 https://irepository.uniten.edu.my/handle/123456789/22146 6814501 613 618 IEEE Computer Society Scopus
institution Universiti Tenaga Nasional
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country Malaysia
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description This paper presents a new hybrid optimisation technique for voltage stability prediction called Artificial Immune Least Square Support Vector Machine (AILSVM). In this paper, a newly developed index named as Voltage Stability Condition Indicator (VSCI) was used to assess the stability condition of load buses in a system. VSCI was derived from a current equation in a complex form of a general 2-bus system. Support Vector Machine (SVM) has been proven to be a powerful tool for solving numerous problems in many fields. However, in order to obtain its best performance, a right combination of SVM parameters is needed. Therefore, Artificial Immune System (AIS) was used as the evolutionary search technique to optimise the value of SVM parameters. The simulations were carried out in a steady state analysis and the data generated were trained and tested under various types of loading conditions either due to an increase in active and/or reactive power. The obtained results show that the proposed methods can successfully give a very good prediction with the predicted values very close to the actual value. All simulations were tested on IEEE 30 bus Reliability Test Systems (RTS). © 2014 IEEE.
author2 57221906825
author_facet 57221906825
Abaziz N.F.
Rahman T.K.A.
Zakaria Z.
format Conference Paper
author Abaziz N.F.
Rahman T.K.A.
Zakaria Z.
spellingShingle Abaziz N.F.
Rahman T.K.A.
Zakaria Z.
Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM)
author_sort Abaziz N.F.
title Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM)
title_short Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM)
title_full Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM)
title_fullStr Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM)
title_full_unstemmed Voltage stability prediction by using Artificial Immune Least Square Support Vector Machines (AILSVM)
title_sort voltage stability prediction by using artificial immune least square support vector machines (ailsvm)
publisher IEEE Computer Society
publishDate 2023
_version_ 1806427956848885760
score 13.222552