Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm

Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computati...

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Main Authors: Suganthan, P. N., Zhang, Xuexia, Chen, Weirong
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Online Access:https://hdl.handle.net/10356/96755
http://hdl.handle.net/10220/13078
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-967552020-03-07T13:24:47Z Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm Suganthan, P. N. Zhang, Xuexia Chen, Weirong School of Electrical and Electronic Engineering International Conference on Intelligent System Design and Engineering Application (2nd : 2012 : Sanya, China) Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computational intelligence-based methods such as genetic algorithms (GAs), differential evolution (DE) algorithms, particle swarm optimization (PSO) algorithms and immune algorithms (IAs) have been applied to solve this problem. This paper employs dynamic multi-group self-adaptive differential evolution (DMSDE) algorithm to solve multi-objective reactive power optimization problem. In DMSDE, the population is divided into multiple groups which exchange information dynamically. Further, in the mutation phase, the best vector among the three randomly vectors is used as the base vector while the difference vector is determined by the remaining two vectors. Moreover, two parameters, F and CR, are self-adapted. The presented method is tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus power systems. The numerical results, when compared with other algorithms, show that DMSDE is an efficient tool to solve dispatch reactive power flow problem. 2013-08-12T08:28:04Z 2019-12-06T19:34:35Z 2013-08-12T08:28:04Z 2019-12-06T19:34:35Z 2012 2012 Conference Paper https://hdl.handle.net/10356/96755 http://hdl.handle.net/10220/13078 10.1109/ISdea.2012.412 en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
description Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computational intelligence-based methods such as genetic algorithms (GAs), differential evolution (DE) algorithms, particle swarm optimization (PSO) algorithms and immune algorithms (IAs) have been applied to solve this problem. This paper employs dynamic multi-group self-adaptive differential evolution (DMSDE) algorithm to solve multi-objective reactive power optimization problem. In DMSDE, the population is divided into multiple groups which exchange information dynamically. Further, in the mutation phase, the best vector among the three randomly vectors is used as the base vector while the difference vector is determined by the remaining two vectors. Moreover, two parameters, F and CR, are self-adapted. The presented method is tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus power systems. The numerical results, when compared with other algorithms, show that DMSDE is an efficient tool to solve dispatch reactive power flow problem.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Suganthan, P. N.
Zhang, Xuexia
Chen, Weirong
format Conference or Workshop Item
author Suganthan, P. N.
Zhang, Xuexia
Chen, Weirong
spellingShingle Suganthan, P. N.
Zhang, Xuexia
Chen, Weirong
Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
author_sort Suganthan, P. N.
title Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
title_short Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
title_full Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
title_fullStr Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
title_full_unstemmed Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
title_sort optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
publishDate 2013
url https://hdl.handle.net/10356/96755
http://hdl.handle.net/10220/13078
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