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Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimization

Indonesian Journal of Electical Engineering and Informatics (IJEEI) · Vol. 2 No. 3 (2014) · hlm. 111–118

DOI
10.52549/ijeei.v2i3.111
ISSN
2089-3272, 2089-3272
Terbit
2014-09-01
Penerbit
IAES Indonesian Section
Bahasa
en

Abstrak

This paper presents, an Adaptive Cat Swarm Optimization (ACSO) for solving reactive power dispatch problem. Cat Swarm Optimization (CSO) is one of the new-fangled swarm intelligence algorithms for finding the most excellent global solution. Because of complication, sometimes conventional CSO takes a lengthy time to converge and cannot attain the precise solution. For solving reactive power dispatch problem and to improve the convergence accuracy level, we propose a new adaptive CSO namely ‘Adaptive Cat Swarm Optimization’ (ACSO). First, we take account of a new-fangled adaptive inertia weight to velocity equation and then employ an adaptive acceleration coefficient. Second, by utilizing the information of two previous or next dimensions and applying a new-fangled factor, we attain to a new position update equation composing the average of position and velocity information. The projected ACSO has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the high-quality performance of the planned algorithm in tumbling the real power loss.

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  • Prasad V. Potluri Siddhartha Institute of Technology
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Rekan penulisOrganisasiArtikel bersama
M.Surya KalavathiAfiliasi tidak diketahui3
B. Ravindhranath ReddyAfiliasi tidak diketahui2
Lenin KanagasabaiAfiliasi tidak diketahui1
K. LeninPrasad V. Potluri Siddhartha Institute of Technology1

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Sumber metadata: OAI-PMH (metadata jurnal) http://section.iaesonline.com/index.php/IJEEI/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">Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimization</dc:title>
	<dc:creator xml:lang="en">Lenin, Kanagasabai</dc:creator>
	<dc:creator xml:lang="en">Reddy, B.Ravindranath</dc:creator>
	<dc:subject xml:lang="en">Optimal Reactive Power</dc:subject>
	<dc:subject xml:lang="en">Transmission loss</dc:subject>
	<dc:subject xml:lang="en">Adaptive cat swarm optimization.</dc:subject>
	<dc:description xml:lang="en">This paper presents, an Adaptive Cat Swarm Optimization (ACSO) for solving reactive power dispatch problem. Cat Swarm Optimization (CSO) is one of the new-fangled swarm intelligence algorithms for finding the most excellent global solution. Because of complication, sometimes conventional CSO takes a lengthy time to converge and cannot attain the precise solution. For solving reactive power dispatch problem and to improve the convergence accuracy level, we propose a new adaptive CSO namely ‘Adaptive Cat Swarm Optimization’ (ACSO). First, we take account of a new-fangled adaptive inertia weight to velocity equation and then employ an adaptive acceleration coefficient. Second, by utilizing the information of two previous or next dimensions and applying a new-fangled factor, we attain to a new position update equation composing the average of position and velocity information. The projected ACSO has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the high-quality performance of the planned algorithm in tumbling the real power loss.</dc:description>
	<dc:publisher xml:lang="en">IAES Indonesian Section</dc:publisher>
	<dc:date>2014-09-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://section.iaesonline.com/index.php/IJEEI/article/view/111</dc:identifier>
	<dc:identifier>10.52549/ijeei.v2i3.111</dc:identifier>
	<dc:source xml:lang="en">Indonesian Journal of Electrical Engineering and Informatics (IJEEI); Vol. 2 No. 3: September 2014; 111-118</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://section.iaesonline.com/index.php/IJEEI/article/view/111/59</dc:relation>
</oai_dc:dc>