LAPSE:2019.1324
Published Article
LAPSE:2019.1324
The State of Art in Particle Swarm Optimization Based Unit Commitment: A Review
Gad Shaari, Neyre Tekbiyik-Ersoy, Mustafa Dagbasi
December 10, 2019
Unit Commitment (UC) requires the optimization of the operation of generation units with varying loads, at every hour, under different technical and environmental constraints. Many solution techniques were developed for the UC problem, and the researchers are still working on improving the efficiency of these techniques. Particle swarm optimization (PSO) is an effective and efficient technique used for solving the UC problems, and it has gotten a considerable amount of attention in recent years. This study provides a state-of-the-art literature review on UC studies utilizing PSO or PSO-variant algorithms, by focusing on research articles published in the last decade. In this study, these algorithms/methods, objectives, constraints are reviewed, with focus on the UC problems that include at least one of the wind and solar technologies, along with thermal unit(s). Although, conventional PSO is one of the most effective techniques used in solving UC problem, other methods were also developed in literature to improve the convergence. In this study, these methods are grouped as extended PSO, modified PSO, and PSO with other techniques. This study shows that PSO with other techniques are utilized more than any other methods. In terms of constraints, it was observed that there are only few studies that considered Transmission Line (TL), Fuel (F), Emission (E), Storage (St) and Crew (Cr) constraints, while Power Balance (PB), Generation limit (GL), Unit minimum Up or Down Time (U/DT), Ramp Up or Ramp Down Time (R-U/DT) and system Spinning Reserve (SR) were the most utilized constraints in UC problems considering wind/solar as a renewable source. In addition, most of the studies are based on a single objective function (cost minimization) and, few of them are multi-objective (cost and emission minimization) based studies.
Keywords
Particle Swarm Optimization, solar, thermal, unit commitment, Wind
Suggested Citation
Shaari G, Tekbiyik-Ersoy N, Dagbasi M. The State of Art in Particle Swarm Optimization Based Unit Commitment: A Review. (2019). LAPSE:2019.1324
Author Affiliations
Shaari G: Energy Systems Engineering Program, Faculty of Engineering, Cyprus International University, Haspolat/Nicosia 99258, Mersin 10, Turkey
Tekbiyik-Ersoy N: Energy Systems Engineering Program, Faculty of Engineering, Cyprus International University, Haspolat/Nicosia 99258, Mersin 10, Turkey
Dagbasi M: Energy Systems Engineering Program, Faculty of Engineering, Cyprus International University, Haspolat/Nicosia 99258, Mersin 10, Turkey
Journal Name
Processes
Volume
7
Issue
10
Article Number
E733
Year
2019
Publication Date
2019-10-14
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr7100733, Publication Type: Review
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LAPSE:2019.1324
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doi:10.3390/pr7100733
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Dec 10, 2019
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Dec 10, 2019
 
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Calvin Tsay
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