Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)

Present days, Power System operates in a stressed condition due to reactive power shortage. Hence, this research involves development of an adaptive mutation algorithm based multi-objective for Optimal Reactive Power Dispatch (ORPD) in a power system in order to minimize the total loss and the...

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Main Authors:	Mahaletchumi, Morgan, Nor Rul Hasma, Abdullah, M. H., Sulaiman, Mahfuzah, Mustafa, Rosdiyana, Samad
Format:	Article
Language:	English
Published:	JES 2016
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/6743/ http://umpir.ump.edu.my/id/eprint/6743/ http://umpir.ump.edu.my/id/eprint/6743/1/fkee-2016-herwan-Benchmark%20studies%20on%20Optimal%20Reactive%20Power.pdf

id	ump-6743
recordtype	eprints
spelling	ump-67432018-04-11T01:28:52Z http://umpir.ump.edu.my/id/eprint/6743/ Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO) Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad TK Electrical engineering. Electronics Nuclear engineering Present days, Power System operates in a stressed condition due to reactive power shortage. Hence, this research involves development of an adaptive mutation algorithm based multi-objective for Optimal Reactive Power Dispatch (ORPD) in a power system in order to minimize the total loss and the improved voltage stability simultaneously. The performance of a Multi-Objective Evolutionary Programming (MOEP) is significantly dependent on the parameter setting of the operator. These parameters tend to change the characteristic of adaptive in different stages of evolutionary process. The intention of this paper is to create adaptive controls for each parameter existing in MOEP where it is able to improve even more the performance of the evolutionary programming. Hence, in this paper, an adaptive mutation operator based multi-objective evolutionary programming is presented. A computer program was written in MATLAB. At the end, the result was compared with the Polynomial Mutation Operator. JES 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6743/1/fkee-2016-herwan-Benchmark%20studies%20on%20Optimal%20Reactive%20Power.pdf Mahaletchumi, Morgan and Nor Rul Hasma, Abdullah and M. H., Sulaiman and Mahfuzah, Mustafa and Rosdiyana, Samad (2016) Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO). Journal of Electrical Systems, 12 (1). pp. 121-132. ISSN 1112-5209 http://journal.esrgroups.org/jes/papers/12_1_8.pdf
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
description	Present days, Power System operates in a stressed condition due to reactive power shortage. Hence, this research involves development of an adaptive mutation algorithm based multi-objective for Optimal Reactive Power Dispatch (ORPD) in a power system in order to minimize the total loss and the improved voltage stability simultaneously. The performance of a Multi-Objective Evolutionary Programming (MOEP) is significantly dependent on the parameter setting of the operator. These parameters tend to change the characteristic of adaptive in different stages of evolutionary process. The intention of this paper is to create adaptive controls for each parameter existing in MOEP where it is able to improve even more the performance of the evolutionary programming. Hence, in this paper, an adaptive mutation operator based multi-objective evolutionary programming is presented. A computer program was written in MATLAB. At the end, the result was compared with the Polynomial Mutation Operator.
format	Article
author	Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad
author_facet	Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad
author_sort	Mahaletchumi, Morgan
title	Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_short	Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_full	Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_fullStr	Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_full_unstemmed	Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_sort	benchmark studies on optimal reactive power dispatch (orpd) based multi-objective evolutionary programming (moep) using mutation based on adaptive mutation operator (amo) and polynomial mutation operator (pmo)
publisher	JES
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/6743/ http://umpir.ump.edu.my/id/eprint/6743/ http://umpir.ump.edu.my/id/eprint/6743/1/fkee-2016-herwan-Benchmark%20studies%20on%20Optimal%20Reactive%20Power.pdf
first_indexed	2023-09-18T22:02:46Z
last_indexed	2023-09-18T22:02:46Z
_version_	1777414508865650688

Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)

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