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Active Power Loss Reduction by Particle Swarm Optimization Algorithm

Kanagasabai Lenin1

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 904-906, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.904906

Online published on Jan 31, 2019

Copyright © Kanagasabai Lenin . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Kanagasabai Lenin, “Active Power Loss Reduction by Particle Swarm Optimization Algorithm,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.904-906, 2019.

MLA Style Citation: Kanagasabai Lenin "Active Power Loss Reduction by Particle Swarm Optimization Algorithm." International Journal of Computer Sciences and Engineering 7.1 (2019): 904-906.

APA Style Citation: Kanagasabai Lenin, (2019). Active Power Loss Reduction by Particle Swarm Optimization Algorithm. International Journal of Computer Sciences and Engineering, 7(1), 904-906.

BibTex Style Citation:
@article{Lenin_2019,
author = {Kanagasabai Lenin},
title = {Active Power Loss Reduction by Particle Swarm Optimization Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {904-906},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3606},
doi = {https://doi.org/10.26438/ijcse/v7i1.904906}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.904906}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3606
TI - Active Power Loss Reduction by Particle Swarm Optimization Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - Kanagasabai Lenin
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 904-906
IS - 1
VL - 7
SN - 2347-2693
ER -

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Abstract

This work presents Particle swarm optimization (PSO) algorithm for solving optimal reactive power problem. PSO is an optimization tool based on a population, where each member is seen as a particle, and each particle is a potential solution to the problem under analysis. Each particle in PSO has a randomized velocity associated to it, which moves through the space of the problem. However, unlike genetic algorithms, PSO does not have operators, such as crossover and mutation. PSO does not implement the survival of the fittest individuals; rather, it implements the simulation of social behaviour. Projected Particle swarm optimization (PSO) algorithm has been tested in standard IEEE 300 bus system and simulation results show the better performance of the proposed algorithm in reducing the real power loss.

Key-Words / Index Term

Optimal reactive power, Transmission loss, particle swarm optimization

References

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