Staff View: Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints

Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints

The main goal behind the combined economic emission dispatch (CEED) is to reduce the costs incurred upon fuel and emission for the generating units available without any intention to violate the generator and security constraints. Hence, the CEED must be handled after considering two challenging goa...

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Main Authors:	Rajagopalan, A., Kasinathan, P., Nagarajan, K., Ramachandaramurthy, V.K., Sengoden, V., Alavandar, S.
Format:	Article
Language:	English
Published:	2020
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id	my.uniten.dspace-13349
record_format	dspace
spelling	my.uniten.dspace-133492020-08-17T06:18:15Z Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints Rajagopalan, A. Kasinathan, P. Nagarajan, K. Ramachandaramurthy, V.K. Sengoden, V. Alavandar, S. The main goal behind the combined economic emission dispatch (CEED) is to reduce the costs incurred upon fuel and emission for the generating units available without any intention to violate the generator and security constraints. Hence, the CEED must be handled after considering two challenging goals such as the costs involved with emission and fuel. In this paper, chaotic self-adaptive interior search algorithm (CSAISA) was proposed to solve the CEED problems, considering the nonlinear behavior of generators in terms of valve point effects, prohibited operating zones, and security constraints. The proposed algorithm was tested for its effectiveness using 11-generating units (without security), IEEE-30 bus system, and IEEE-118 bus system with security constraints. The results of the proposed CSAISA were compared with interior search algorithm (ISA), harmony search algorithm (HSA), differential evolution (DE), particle swarm optimization (PSO), and genetic algorithm (GA). To conclude, the proposed CSAISA outperformed all other algorithms in terms of convergence speed, implementation time, and solution quality, which was tested using performance metrics. © 2019 John Wiley & Sons, Ltd. 2020-02-03T03:32:00Z 2020-02-03T03:32:00Z 2019-03 Article 10.1002/2050-7038.12026 en
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
language	English
description	The main goal behind the combined economic emission dispatch (CEED) is to reduce the costs incurred upon fuel and emission for the generating units available without any intention to violate the generator and security constraints. Hence, the CEED must be handled after considering two challenging goals such as the costs involved with emission and fuel. In this paper, chaotic self-adaptive interior search algorithm (CSAISA) was proposed to solve the CEED problems, considering the nonlinear behavior of generators in terms of valve point effects, prohibited operating zones, and security constraints. The proposed algorithm was tested for its effectiveness using 11-generating units (without security), IEEE-30 bus system, and IEEE-118 bus system with security constraints. The results of the proposed CSAISA were compared with interior search algorithm (ISA), harmony search algorithm (HSA), differential evolution (DE), particle swarm optimization (PSO), and genetic algorithm (GA). To conclude, the proposed CSAISA outperformed all other algorithms in terms of convergence speed, implementation time, and solution quality, which was tested using performance metrics. © 2019 John Wiley & Sons, Ltd.
format	Article
author	Rajagopalan, A. Kasinathan, P. Nagarajan, K. Ramachandaramurthy, V.K. Sengoden, V. Alavandar, S.
spellingShingle	Rajagopalan, A. Kasinathan, P. Nagarajan, K. Ramachandaramurthy, V.K. Sengoden, V. Alavandar, S. Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints
author_facet	Rajagopalan, A. Kasinathan, P. Nagarajan, K. Ramachandaramurthy, V.K. Sengoden, V. Alavandar, S.
author_sort	Rajagopalan, A.
title	Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints
title_short	Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints
title_full	Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints
title_fullStr	Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints
title_full_unstemmed	Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints
title_sort	chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints
publishDate	2020
_version_	1678595900621979648
score	13.222552

Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints

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