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    Abstract
2016 (Vol. 13, Issue: 8)
Research Article

Optimal DG Allocation in Distribution Networks using Cat Swarm Optimization

1Neeraj Kanwar, 1Nikhil Gupta, 2K.R. Niazi and 1Anil Swarnkar
1Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, India
2Department of Electrical Engineering, Faculty of Engineering, Talibah University, Madinah, KSA
 

DOI: 10.19026/rjaset.13.3048
Submitted Accepted Published
June ‎12, ‎2015 July ‎8, ‎2015 October 15, 2016

  How to Cite this Article:

1Neeraj Kanwar, 1Nikhil Gupta, 2K.R. Niazi and 1Anil Swarnkar, 2016. Optimal DG Allocation in Distribution Networks using Cat Swarm Optimization.  Research Journal of Applied Sciences, Engineering and Technology, 13(8): 626-631.

DOI: 10.19026/rjaset.13.3048

URL: http://www.maxwellsci.com/jp/mspabstract.php?jid=RJASET&doi=rjaset.13.3048

Abstract:


Dispersed or Distributed Generations (DGs) are becoming more popular on account of socio-economic reasons and also to enhance performance of distribution systems. Cat Swarm Optimization (CSO) is one of the recent swarm-intelligence-based optimization techniques which provides local and global search simultaneously. The aim of this study is to introduce the application of CSO method for optimal allocation of DGs in distribution networks. The problem is formulated to maximize annual energy loss reduction and to maintain a better node voltage profile under piece-wise multi-level load profile using penalty factor approach. Modification is suggested in CSO to enhance its exploration and exploitation potentials. In addition, clever search is proposed to enhance overall performance of the optimizing tool. The proposed method is applied on the benchmark IEEE 33-bus and 69-bus system and the obtained results are promising.

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    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.

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© The Author(s) 2016

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