Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm

Differential evolution (DE) algorithm is used to determine optimal location of unified power quality conditioner (UPQC) considering its size in the radial distribution systems. The problem is formulated to find the optimum location of UPQC based on an objective function (OF) defined for improving of...

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Main Authors: Seyed Abbas Taher, Seyed Ahmadreza Afsari
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2012/838629
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spelling doaj-01b3179128f34a3ea7d4595048dad4ac2020-11-25T00:11:24ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/838629838629Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution AlgorithmSeyed Abbas Taher0Seyed Ahmadreza Afsari1Department of Electrical Engineering, Faculty of Engineering, University of Kashan, Kashan 87317-51167, IranDepartment of Electrical Engineering, Faculty of Engineering, University of Kashan, Kashan 87317-51167, IranDifferential evolution (DE) algorithm is used to determine optimal location of unified power quality conditioner (UPQC) considering its size in the radial distribution systems. The problem is formulated to find the optimum location of UPQC based on an objective function (OF) defined for improving of voltage and current profiles, reducing power loss and minimizing the investment costs considering the OF's weighting factors. Hence, a steady-state model of UPQC is derived to set in forward/backward sweep load flow. Studies are performed on two IEEE 33-bus and 69-bus standard distribution networks. Accuracy was evaluated by reapplying the procedures using both genetic (GA) and immune algorithms (IA). Comparative results indicate that DE is capable of offering a nearer global optimal in minimizing the OF and reaching all the desired conditions than GA and IA.http://dx.doi.org/10.1155/2012/838629
collection DOAJ
language English
format Article
sources DOAJ
author Seyed Abbas Taher
Seyed Ahmadreza Afsari
spellingShingle Seyed Abbas Taher
Seyed Ahmadreza Afsari
Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm
Mathematical Problems in Engineering
author_facet Seyed Abbas Taher
Seyed Ahmadreza Afsari
author_sort Seyed Abbas Taher
title Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm
title_short Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm
title_full Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm
title_fullStr Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm
title_full_unstemmed Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm
title_sort optimal location and sizing of upqc in distribution networks using differential evolution algorithm
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2012-01-01
description Differential evolution (DE) algorithm is used to determine optimal location of unified power quality conditioner (UPQC) considering its size in the radial distribution systems. The problem is formulated to find the optimum location of UPQC based on an objective function (OF) defined for improving of voltage and current profiles, reducing power loss and minimizing the investment costs considering the OF's weighting factors. Hence, a steady-state model of UPQC is derived to set in forward/backward sweep load flow. Studies are performed on two IEEE 33-bus and 69-bus standard distribution networks. Accuracy was evaluated by reapplying the procedures using both genetic (GA) and immune algorithms (IA). Comparative results indicate that DE is capable of offering a nearer global optimal in minimizing the OF and reaching all the desired conditions than GA and IA.
url http://dx.doi.org/10.1155/2012/838629
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