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Result Analysis for Particle Swarm Optimization and Genetic Algorithm for Load Flow Study

Poulami Ghosh1 , Anand Gopal Mukherjee2 , Siddharth Kumar Singh3 , Hari Prasad Dubey4

Section:Research Paper, Product Type: Journal Paper
Volume-04 , Issue-06 , Page no. 99-105, Aug-2016

Online published on Sep 03, 2016

Copyright © Poulami Ghosh, Anand Gopal Mukherjee, Siddharth Kumar Singh, Hari Prasad Dubey . 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: Poulami Ghosh, Anand Gopal Mukherjee, Siddharth Kumar Singh, Hari Prasad Dubey, “Result Analysis for Particle Swarm Optimization and Genetic Algorithm for Load Flow Study,” International Journal of Computer Sciences and Engineering, Vol.04, Issue.06, pp.99-105, 2016.

MLA Style Citation: Poulami Ghosh, Anand Gopal Mukherjee, Siddharth Kumar Singh, Hari Prasad Dubey "Result Analysis for Particle Swarm Optimization and Genetic Algorithm for Load Flow Study." International Journal of Computer Sciences and Engineering 04.06 (2016): 99-105.

APA Style Citation: Poulami Ghosh, Anand Gopal Mukherjee, Siddharth Kumar Singh, Hari Prasad Dubey, (2016). Result Analysis for Particle Swarm Optimization and Genetic Algorithm for Load Flow Study. International Journal of Computer Sciences and Engineering, 04(06), 99-105.

BibTex Style Citation:
@article{Ghosh_2016,
author = {Poulami Ghosh, Anand Gopal Mukherjee, Siddharth Kumar Singh, Hari Prasad Dubey},
title = {Result Analysis for Particle Swarm Optimization and Genetic Algorithm for Load Flow Study},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2016},
volume = {04},
Issue = {06},
month = {8},
year = {2016},
issn = {2347-2693},
pages = {99-105},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=131},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=131
TI - Result Analysis for Particle Swarm Optimization and Genetic Algorithm for Load Flow Study
T2 - International Journal of Computer Sciences and Engineering
AU - Poulami Ghosh, Anand Gopal Mukherjee, Siddharth Kumar Singh, Hari Prasad Dubey
PY - 2016
DA - 2016/09/03
PB - IJCSE, Indore, INDIA
SP - 99-105
IS - 06
VL - 04
SN - 2347-2693
ER -

           

Abstract

This paper presents a comparative study between Particle Swarm optimization and Genetic Algorithm based methodology for solving load flow in electrical power systems. Load flow study provides the system status in steady-state and is required by several functions performed in power system control rooms.

Key-Words / Index Term

Particle swarm optimization, Genetic Algorithm, Load flow, Electrical Power System, Score

References

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