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...

Full description

Bibliographic Details
Main Authors: Mahaletchumi, Morgan, Nor Rul Hasma, Abdullah, M. H., Sulaiman, Mahfuzah, Mustafa, Rosdiyana, Samad
Format: Article
Language:English
Published: JES 2016
Subjects:
Online Access: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
_version_ 1848817844281671680
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
building UMP Institutional Repository
collection Online Access
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.
first_indexed 2025-11-15T01:28:13Z
format Article
id ump-6743
institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T01:28:13Z
publishDate 2016
publisher JES
recordtype eprints
repository_type Digital Repository
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. (Published) http://journal.esrgroups.org/jes/papers/12_1_8.pdf
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)
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_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_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_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)
topic TK Electrical engineering. Electronics Nuclear engineering
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