Dynamic economic dispatch assessment using particle swarm optimization technique

This paper presents the application of Particle Swarm Optimization (PSO) technique for solving the Dynamic Economic Dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation...

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Published in:Bulletin of Electrical Engineering and Informatics
Main Author: Othman M.M.; Salim M.A.I.; Musirin I.; Salim N.A.; Othman M.L.
Format: Article
Language:English
Published: Institute of Advanced Engineering and Science 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052715809&doi=10.11591%2feei.v7i3.1278&partnerID=40&md5=afda2a7fbb32d426e914c47684ca16b7
id 2-s2.0-85052715809
spelling 2-s2.0-85052715809
Othman M.M.; Salim M.A.I.; Musirin I.; Salim N.A.; Othman M.L.
Dynamic economic dispatch assessment using particle swarm optimization technique
2018
Bulletin of Electrical Engineering and Informatics
7
3
10.11591/eei.v7i3.1278
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052715809&doi=10.11591%2feei.v7i3.1278&partnerID=40&md5=afda2a7fbb32d426e914c47684ca16b7
This paper presents the application of Particle Swarm Optimization (PSO) technique for solving the Dynamic Economic Dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines. Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved.
Institute of Advanced Engineering and Science
20893191
English
Article
All Open Access; Green Open Access
author Othman M.M.; Salim M.A.I.; Musirin I.; Salim N.A.; Othman M.L.
spellingShingle Othman M.M.; Salim M.A.I.; Musirin I.; Salim N.A.; Othman M.L.
Dynamic economic dispatch assessment using particle swarm optimization technique
author_facet Othman M.M.; Salim M.A.I.; Musirin I.; Salim N.A.; Othman M.L.
author_sort Othman M.M.; Salim M.A.I.; Musirin I.; Salim N.A.; Othman M.L.
title Dynamic economic dispatch assessment using particle swarm optimization technique
title_short Dynamic economic dispatch assessment using particle swarm optimization technique
title_full Dynamic economic dispatch assessment using particle swarm optimization technique
title_fullStr Dynamic economic dispatch assessment using particle swarm optimization technique
title_full_unstemmed Dynamic economic dispatch assessment using particle swarm optimization technique
title_sort Dynamic economic dispatch assessment using particle swarm optimization technique
publishDate 2018
container_title Bulletin of Electrical Engineering and Informatics
container_volume 7
container_issue 3
doi_str_mv 10.11591/eei.v7i3.1278
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052715809&doi=10.11591%2feei.v7i3.1278&partnerID=40&md5=afda2a7fbb32d426e914c47684ca16b7
description This paper presents the application of Particle Swarm Optimization (PSO) technique for solving the Dynamic Economic Dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines. Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved.
publisher Institute of Advanced Engineering and Science
issn 20893191
language English
format Article
accesstype All Open Access; Green Open Access
record_format scopus
collection Scopus
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