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Reseach Article

Placement and Sizing of Distributed Generation on Distribution Systems with a Multi-Objective Particle Swarm Optimization and Analytical Approach: A Review

by Pooja Shivwanshi, Sameena Elias Mubeen
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 161 - Number 12
Year of Publication: 2017
Authors: Pooja Shivwanshi, Sameena Elias Mubeen
10.5120/ijca2017913111

Pooja Shivwanshi, Sameena Elias Mubeen . Placement and Sizing of Distributed Generation on Distribution Systems with a Multi-Objective Particle Swarm Optimization and Analytical Approach: A Review. International Journal of Computer Applications. 161, 12 ( Mar 2017), 21-24. DOI=10.5120/ijca2017913111

@article{ 10.5120/ijca2017913111,
author = { Pooja Shivwanshi, Sameena Elias Mubeen },
title = { Placement and Sizing of Distributed Generation on Distribution Systems with a Multi-Objective Particle Swarm Optimization and Analytical Approach: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 161 },
number = { 12 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 21-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume161/number12/27200-2017913111/ },
doi = { 10.5120/ijca2017913111 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:07:18.894645+05:30
%A Pooja Shivwanshi
%A Sameena Elias Mubeen
%T Placement and Sizing of Distributed Generation on Distribution Systems with a Multi-Objective Particle Swarm Optimization and Analytical Approach: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 161
%N 12
%P 21-24
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Distributed generations (DGs) have number of benefits in the electric power industry, such as improvement of voltage stability, enhancement of reliability and power quality. This paper compares the DG placement result of analytical approach with the Multi-Objective Particle Swarm Optimization (MOPSO). The analytical method is based on a formulation for the power flow problem. A priority is loss sensitivity to determine the best locations of applicant distributed generation units. The multi-objective particle swarm optimization determines the optimal DGs places and sizes. The MOPSO improves voltage profile and stability, power-loss reduction, and reliability enhancement. The results show that the analytical method could lead to optimal or near-optimal result, while requiring lower computational effort.

References
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Index Terms

Computer Science
Information Sciences

Keywords

DG placement DG sizing distributed generation Analytical optimization method multiobjective particle swarm optimization (MOPSO).