Economic dispatch by optimization techniques
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| Titel: | Economic dispatch by optimization techniques |
|---|---|
| Autoren: | Ali Abttan, Rana, Hasan Tawafan, Adnan, Jaafar Ismael, Samar |
| Quelle: | International Journal of Electrical and Computer Engineering (IJECE); Vol 12, No 3: June 2022; 2228-2241 ; 2722-2578 ; 2088-8708 ; 10.11591/ijece.v12i3 |
| Verlagsinformationen: | Institute of Advanced Engineering and Science |
| Publikationsjahr: | 2022 |
| Schlagwörter: | ant lion optimization, bat algorithm optimization, economic dispatch, IEEE-30 |
| Beschreibung: | The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic approaches are introduced, the BA and ALOA. A rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA. The ALOA imitates ant lions' hunting process. The introduction of a numerical description of its biological actions for the solution of ED in the power framework. These algorithms are applied to two systems: a small scale three generator system and a large scale six generator. Results show were compared on the metrics of convergence rate, cost, and average run time that the ALOA and BA are suitable for economic dispatch studies which is clear in the comparison set with other algorithms. Both of these algorithms are tested on IEEE-30 bus reliability test system. |
| Publikationsart: | article in journal/newspaper |
| Dateibeschreibung: | application/pdf |
| Sprache: | English |
| Relation: | https://ijece.iaescore.com/index.php/IJECE/article/view/25989/15602; https://ijece.iaescore.com/index.php/IJECE/article/view/25989 |
| DOI: | 10.11591/ijece.v12i3.pp2228-2241 |
| Verfügbarkeit: | https://ijece.iaescore.com/index.php/IJECE/article/view/25989 https://doi.org/10.11591/ijece.v12i3.pp2228-2241 |
| Rights: | Copyright (c) 2021 Rana Ali Abttan, Adnan Hasan Tawafan, Samar Jaafar Ismael ; http://creativecommons.org/licenses/by-sa/4.0 |
| Dokumentencode: | edsbas.1AC5EF69 |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic approaches are introduced, the BA and ALOA. A rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA. The ALOA imitates ant lions' hunting process. The introduction of a numerical description of its biological actions for the solution of ED in the power framework. These algorithms are applied to two systems: a small scale three generator system and a large scale six generator. Results show were compared on the metrics of convergence rate, cost, and average run time that the ALOA and BA are suitable for economic dispatch studies which is clear in the comparison set with other algorithms. Both of these algorithms are tested on IEEE-30 bus reliability test system. |
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| DOI: | 10.11591/ijece.v12i3.pp2228-2241 |