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A review on economic emission dispatch problems using quantum computational intelligence

Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limitation of natural resources and global warming make this topic into the center of discussion and research. This paper reviews the use of Quantum Computational Intelligence (QCI...

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Main Authors: Mahdi, F.P., Vasant, P., Kallimani, V., Abdullah-Al-Wadud, M.
Format: Conference or Workshop Item
Published: American Institute of Physics Inc. 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006048070&doi=10.1063%2f1.4968051&partnerID=40&md5=29888a95c984541d390292d1e1835e46
http://eprints.utp.edu.my/30600/
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spelling my.utp.eprints.306002022-03-25T07:12:05Z A review on economic emission dispatch problems using quantum computational intelligence Mahdi, F.P. Vasant, P. Kallimani, V. Abdullah-Al-Wadud, M. Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limitation of natural resources and global warming make this topic into the center of discussion and research. This paper reviews the use of Quantum Computational Intelligence (QCI) in solving Economic Emission Dispatch problems. QCI techniques like Quantum Genetic Algorithm (QGA) and Quantum Particle Swarm Optimization (QPSO) algorithm are discussed here. This paper will encourage the researcher to use more QCI based algorithm to get better optimal result for solving EED problems. © 2016 Author(s). American Institute of Physics Inc. 2016 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006048070&doi=10.1063%2f1.4968051&partnerID=40&md5=29888a95c984541d390292d1e1835e46 Mahdi, F.P. and Vasant, P. and Kallimani, V. and Abdullah-Al-Wadud, M. (2016) A review on economic emission dispatch problems using quantum computational intelligence. In: UNSPECIFIED. http://eprints.utp.edu.my/30600/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limitation of natural resources and global warming make this topic into the center of discussion and research. This paper reviews the use of Quantum Computational Intelligence (QCI) in solving Economic Emission Dispatch problems. QCI techniques like Quantum Genetic Algorithm (QGA) and Quantum Particle Swarm Optimization (QPSO) algorithm are discussed here. This paper will encourage the researcher to use more QCI based algorithm to get better optimal result for solving EED problems. © 2016 Author(s).
format Conference or Workshop Item
author Mahdi, F.P.
Vasant, P.
Kallimani, V.
Abdullah-Al-Wadud, M.
spellingShingle Mahdi, F.P.
Vasant, P.
Kallimani, V.
Abdullah-Al-Wadud, M.
A review on economic emission dispatch problems using quantum computational intelligence
author_facet Mahdi, F.P.
Vasant, P.
Kallimani, V.
Abdullah-Al-Wadud, M.
author_sort Mahdi, F.P.
title A review on economic emission dispatch problems using quantum computational intelligence
title_short A review on economic emission dispatch problems using quantum computational intelligence
title_full A review on economic emission dispatch problems using quantum computational intelligence
title_fullStr A review on economic emission dispatch problems using quantum computational intelligence
title_full_unstemmed A review on economic emission dispatch problems using quantum computational intelligence
title_sort review on economic emission dispatch problems using quantum computational intelligence
publisher American Institute of Physics Inc.
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006048070&doi=10.1063%2f1.4968051&partnerID=40&md5=29888a95c984541d390292d1e1835e46
http://eprints.utp.edu.my/30600/
_version_ 1738657130439770112
score 13.209306

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