Comparative study on distributed generator sizing using three types of particle swarm optimization
Total power losses in a distribution network can be minimized by installing Distributed Generator (DG) with correct size. In line with this objective, most of the researchers have used multiple types of optimization technique to regulate the DG’s output to compute its optimal size. In this p...
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my.uthm.eprints.80632022-12-06T02:54:51Z http://eprints.uthm.edu.my/8063/ Comparative study on distributed generator sizing using three types of particle swarm optimization Jamian, J. J. Mustafa, M. W. Mokhlis, H. Abdullah, M. N. T Technology (General) Total power losses in a distribution network can be minimized by installing Distributed Generator (DG) with correct size. In line with this objective, most of the researchers have used multiple types of optimization technique to regulate the DG’s output to compute its optimal size. In this paper, a comparative studies of a new proposed Rank Evolutionary Particle Swarm Optimization (REPSO) method with Evolutionary Particle Swarm Optimization (EPSO) and Traditional Particle Swarm Optimization (PSO) is conducted. Both REPSO and EPSO are using the concept of Evolutionary Programming (EP) in Particle Swarm Optimization (PSO) process. The implementation of EP in PSO allows the entire particles to move toward the optimal value faster. A test on determining optimum size of DGs in 69 bus radial distribution system reveals the superiority of REPSO over PSO and EPSO. 2012 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/8063/1/P11002_bd1bafcdcb9b4170570fa16611d2c450.pdf Jamian, J. J. and Mustafa, M. W. and Mokhlis, H. and Abdullah, M. N. (2012) Comparative study on distributed generator sizing using three types of particle swarm optimization. In: 2012 Third International Conference on Intelligent Systems Modelling and Simulation, 8-10 Feb. 2012. https://doi.org/10.1109/ISMS.2012.71 |
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T Technology (General) Jamian, J. J. Mustafa, M. W. Mokhlis, H. Abdullah, M. N. Comparative study on distributed generator sizing using three types of particle swarm optimization |
description |
Total power losses in a distribution network can be
minimized by installing Distributed Generator (DG) with
correct size. In line with this objective, most of the researchers
have used multiple types of optimization technique to regulate
the DG’s output to compute its optimal size. In this paper, a
comparative studies of a new proposed Rank Evolutionary
Particle Swarm Optimization (REPSO) method with
Evolutionary Particle Swarm Optimization (EPSO) and
Traditional Particle Swarm Optimization (PSO) is conducted.
Both REPSO and EPSO are using the concept of Evolutionary
Programming (EP) in Particle Swarm Optimization (PSO)
process. The implementation of EP in PSO allows the entire
particles to move toward the optimal value faster. A test on
determining optimum size of DGs in 69 bus radial distribution
system reveals the superiority of REPSO over PSO and EPSO. |
format |
Conference or Workshop Item |
author |
Jamian, J. J. Mustafa, M. W. Mokhlis, H. Abdullah, M. N. |
author_facet |
Jamian, J. J. Mustafa, M. W. Mokhlis, H. Abdullah, M. N. |
author_sort |
Jamian, J. J. |
title |
Comparative study on distributed generator sizing using three types of particle swarm optimization |
title_short |
Comparative study on distributed generator sizing using three types of particle swarm optimization |
title_full |
Comparative study on distributed generator sizing using three types of particle swarm optimization |
title_fullStr |
Comparative study on distributed generator sizing using three types of particle swarm optimization |
title_full_unstemmed |
Comparative study on distributed generator sizing using three types of particle swarm optimization |
title_sort |
comparative study on distributed generator sizing using three types of particle swarm optimization |
publishDate |
2012 |
url |
http://eprints.uthm.edu.my/8063/1/P11002_bd1bafcdcb9b4170570fa16611d2c450.pdf http://eprints.uthm.edu.my/8063/ https://doi.org/10.1109/ISMS.2012.71 |
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1751538652847013888 |