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Polar wolf optimization algorithm for solving optimal reactive power problem

International Journal of Applied Power Engineering (IJAPE) · Vol. 9 No. 2 (2020) · hlm. 107–112

DOI
10.11591/ijape.v9.i2.pp107-112
ISSN
2722-2624, 2252-8792
Terbit
2020-08-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

This paper proposes polar wolf optimization (PWO) algorithm to solve the optimal reactive power problem. Proposed algorithm enthused from actions of polar wolves. Leader’s wolves which denoted as xα are accountable for taking judgment on hunting, resting place, time to awaken etc. second level is xβ those acts when there is need of substitute in first case. Then xγ be as final level of the wolves. In the modeling social hierarchy is developed to discover the most excellent solutions acquired so far. Then the encircling method is used to describe circle-shaped vicinity around every candidate solutions. In order to agents work in a binary space, the position modernized accordingly. Proposed PWO algorithm has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show the projected algorithms reduced the real power loss considerably.

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijape.iaescore.com/index.php/IJAPE/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Polar wolf optimization algorithm for solving optimal reactive power problem</dc:title>
	<dc:creator>Lenin, Kanagasabai</dc:creator>
	<dc:description xml:lang="en-US">This paper proposes polar wolf optimization (PWO) algorithm to solve the optimal reactive power problem. Proposed algorithm enthused from actions of polar wolves. Leader’s wolves which denoted as xα are accountable for taking judgment on hunting, resting place, time to awaken etc. second level is xβ those acts when there is need of substitute in first case. Then xγ be as final level of the wolves. In the modeling social hierarchy is developed to discover the most excellent solutions acquired so far. Then the encircling method is used to describe circle-shaped vicinity around every candidate solutions. In order to agents work in a binary space, the position modernized accordingly. Proposed PWO algorithm has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show the projected algorithms reduced the real power loss considerably.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2020-08-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijape.iaescore.com/index.php/IJAPE/article/view/20244</dc:identifier>
	<dc:identifier>10.11591/ijape.v9.i2.pp107-112</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Applied Power Engineering (IJAPE); Vol 9, No 2: August 2020; 107-112</dc:source>
	<dc:source>2722-2624</dc:source>
	<dc:source>2252-8792</dc:source>
	<dc:source>10.11591/ijape.v9.i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijape.iaescore.com/index.php/IJAPE/article/view/20244/12886</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>