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Volume 5, Issue 5, October 2016, Page: 163-170
Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm
Mohammad Ali Hormozi, Fars Regional Electrical Company, Shiraz, Iran
Mohammad Barghi Jahromi, Fars Regional Electrical Company, Shiraz, Iran
Gholamreza Nasiri, Fars Regional Electrical Company, Shiraz, Iran
Received: Aug. 26, 2016;       Accepted: Sep. 13, 2016;       Published: Oct. 19, 2016
DOI: 10.11648/j.ijepe.20160505.11      View  3827      Downloads  285
Abstract
In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.
Keywords
Distribution Network Reconfiguration, Distributed Generation, Hybrid Algorithm, Meta-Heuristic Algorithm, Binary Particular Swarm Optimization Algorithm, Power Loss
To cite this article
Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri, Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm, International Journal of Energy and Power Engineering. Vol. 5, No. 5, 2016, pp. 163-170. doi: 10.11648/j.ijepe.20160505.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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