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     Research Journal of Applied Sciences, Engineering and Technology


Application of Intelligent Algorithms for Optimal Distributed Generation Allocation to Voltage Profile Improvement and Line Losses Reduction

1Arman Tarrah, 2Rasoul Asghari and 1Masoud Aghazadeh Mehrabani
1Department of Electrical Engineering, Islamic Azad University, Lahijan Branch, Lahijan, Iran
2Department of Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran
Research Journal of Applied Sciences, Engineering and Technology  2013  14:3767-3773
http://dx.doi.org/10.19026/rjaset.5.4522  |  © The Author(s) 2013
Received: September 15, 2012  |  Accepted: November 01, 2012  |  Published: April 20, 2013

Abstract

Distributed Generation (DG) had created a challenge an opportunity for developing various novel technologies in power generation. The rate and of DG implementation have to be determined. The increasing need of electricity and establishing powerhouses, as well as spending a great amount of time to built powerhouses, indicate the necessity of distributed generation in small size and close to the consumer location. In this study selecting IEEE-14 bus systems, attempt to investigate the effect of distributed generation in line losses and voltage profile by using two optimization techniques. The introduction of PSO and CSA base DG in a distribution System offer several benefits: Significant voltage profile improvement, Considerable line loss reduction, improves system reliability and etc. The optimum value of DG, also obtained increasing the maximum load ability of the system. Finally the results are compared to a system with and without installation DGs.

Keywords:

Allocation, distributed generation, loss reduction, particle swarm optimization, voltage profile improvement,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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