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Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm

by Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 3
Year of Publication: 2013
Authors: Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri
10.5120/10611-5327

Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri . Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm. International Journal of Computer Applications. 64, 3 ( February 2013), 1-10. DOI=10.5120/10611-5327

@article{ 10.5120/10611-5327,
author = { Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri },
title = { Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 3 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number3/10611-5327/ },
doi = { 10.5120/10611-5327 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:15:24.802886+05:30
%A Rajneesh K. Karn
%A Yogendra Kumar
%A Gayatri Agnihotri
%T Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 3
%P 1-10
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To restore electricity service in healthy area outside the faulted zone in power distribution system is known as service restoration. In this paper, a technique based on hybrid Genetic Algorithm-Ant Colony Optimization (GA-ACO) is presented for solving the service restoration problem in electric power distribution system. Due the presence of various conflicting objectives and constraints, the task of service restoration is multi-objective and multi-constraint optimization problem. In contrast to conventional optimization technique, this approach does not require tunable weighting factors to convert multiple objectives into equivalent single objective. In this work various practical distribution systems issues such as presence of priority customers, remotely and manually controlled switches etc have been considered as objective functions. Based on simulation results on four different distribution networks, the performance of hybrid GA-ACO is found significantly better than Non Dominated Sorting of Genetic Algorithm-II (NSGA-II) and conventional Genetic Algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Electric power distribution systems Priority customers Ranking based Ant colony optimization Service restoration

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