Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution

Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution

This paper proposes the application of the recent meta-heuristic method namely Ant Lion Optimizer (ALO) in solving Optimal Reactive Power Dispatch (ORPD) problem. The objective is to minimize the transmission losses by finding the best combination of control variables including generator voltages, t...

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Main Authors: Rebecca Ng, Shin Mei, M. H., Sulaiman, Zuriani, Mustaffa
Format: Article
Language:English
Published: JES 2015
Subjects:
QA76 Computer software
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/11955/
http://umpir.ump.edu.my/id/eprint/11955/
http://umpir.ump.edu.my/id/eprint/11955/1/Ant%20lion%20optimizer%20for%20optimal%20reactive%20power%20dispatch%20solution.pdf
id ump-11955
recordtype eprints
spelling ump-119552019-10-30T03:38:23Z http://umpir.ump.edu.my/id/eprint/11955/ Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution Rebecca Ng, Shin Mei M. H., Sulaiman Zuriani, Mustaffa QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering This paper proposes the application of the recent meta-heuristic method namely Ant Lion Optimizer (ALO) in solving Optimal Reactive Power Dispatch (ORPD) problem. The objective is to minimize the transmission losses by finding the best combination of control variables including generator voltages, transformer tap ratios and reactive compensation devices. In order to show the effectiveness of ALO in solving ORPD, IEEE 30-bus system is utilized. The comparison with other methods also reported in this paper. JES 2015 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11955/1/Ant%20lion%20optimizer%20for%20optimal%20reactive%20power%20dispatch%20solution.pdf Rebecca Ng, Shin Mei and M. H., Sulaiman and Zuriani, Mustaffa (2015) Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution. Journal of Electrical Systems, Sp Iss (3). pp. 67-74. ISSN 1112-5209 http://journal.esrgroups.org/jes/papers/AMPE2015_JES_9_.pdf
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA76 Computer software
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle QA76 Computer software
TK Electrical engineering. Electronics Nuclear engineering
Rebecca Ng, Shin Mei
M. H., Sulaiman
Zuriani, Mustaffa
Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution
description This paper proposes the application of the recent meta-heuristic method namely Ant Lion Optimizer (ALO) in solving Optimal Reactive Power Dispatch (ORPD) problem. The objective is to minimize the transmission losses by finding the best combination of control variables including generator voltages, transformer tap ratios and reactive compensation devices. In order to show the effectiveness of ALO in solving ORPD, IEEE 30-bus system is utilized. The comparison with other methods also reported in this paper.
format Article
author Rebecca Ng, Shin Mei
M. H., Sulaiman
Zuriani, Mustaffa
author_facet Rebecca Ng, Shin Mei
M. H., Sulaiman
Zuriani, Mustaffa
author_sort Rebecca Ng, Shin Mei
title Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution
title_short Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution
title_full Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution
title_fullStr Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution
title_full_unstemmed Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution
title_sort ant lion optimizer for optimal reactive power dispatch solution
publisher JES
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/11955/
http://umpir.ump.edu.my/id/eprint/11955/
http://umpir.ump.edu.my/id/eprint/11955/1/Ant%20lion%20optimizer%20for%20optimal%20reactive%20power%20dispatch%20solution.pdf
first_indexed 2023-09-18T22:13:03Z
last_indexed 2023-09-18T22:13:03Z
_version_ 1777415156066680832

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