Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Operation cost reduction in unit commitment problem using improved quantum binary PSO algorithm

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 2 (2020)

DOI
10.11591/ijece.v10i2.pp1149-1155
ISSN
2088-8708, 2088-8708
Published
2020-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Unit Commitment (UC) is a nonlinear mixed integer-programming problem. UC is used to minimize the operational cost of the generation units in a power system by scheduling some of generators in ON state and the other generators in OFF state according to the total power outputs of generation units, load demand and the constraints of power system. This paper proposes an Improved Quantum Binary Particle Swarm Optimization (IQBPSO) algorithm. The tests have been made on a 10-units simulation system and the results show the improvement in an operation cost reduction after using the proposed algorithm compared with the ordinary Quantum Binary Particle Swarm Optimization (QBPSO) algorithm.

Collaboration network of the authors

6 authors · 7 co-authorship links · 4 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Middle Technical University
  • Al-Furat Al-Awsat Technical University
  • Northern Technical University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Waleed Khalid Shakir Al-JuboriAl-Furat Al-Awsat Technical University3
Haider Fathi KadomMiddle Technical University1
Ahmed Jadaan AliNorthern Technical University1
Firas Saaduldeen AhmedMiddle Technical University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref 
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Operation cost reduction in unit commitment problem using improved quantum binary PSO algorithm</dc:title><dc:creator>Hussain, Ali Nasser</dc:creator><dc:creator>Ismail, Ali Abduladheem</dc:creator><dc:description>&lt;jats:p&gt;Unit Commitment (UC) is a nonlinear mixed integer-programming problem. UC is used to minimize the operational cost of the generation units in a power system by scheduling some of generators in ON state and the other generators in OFF state according to the total power outputs of generation units, load demand and the constraints of power system. This paper proposes an Improved Quantum Binary Particle Swarm Optimization (IQBPSO) algorithm. The tests have been made on a 10-units simulation system and the results show the improvement in an operation cost reduction after using the proposed algorithm compared with the ordinary  Quantum Binary Particle Swarm Optimization (QBPSO) algorithm.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v10i2.pp1149-1155</dc:identifier><dc:identifier>10.11591/ijece.v10i2.pp1149-1155</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 2 (2020); 1149</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/20331/pdf</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>