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2013 (Vol. 5, Issue: 14)
Article Information:

Using Intelligent Algorithms to Find the Optimal Placement of Distributed Generation

Arman Tarrah and Masoud Aghazadeh Mehrabani
Corresponding Author:  Arman Tarrah 

Key words:  Distributed generation, hybrid genetic-particle swarm optimization, particle swarm optimization, real power loss, sitting and sizing, voltage profile,
Vol. 5 , (14): 3761-3766
Submitted Accepted Published
September 08, 2012 November 01, 2012 April 20, 2013
Abstract:

This study used Hybrid Genetic-Particle Swarm Optimization (HGPSO) and Particle Swarm Optimization (PSO) for the allocation of Distributed Generation (DG) in order to minimize the total real loss and improve voltage profile in a primary distribution system. The mutation operation of the Genetic Algorithm (GA) is implemented into the Particle Swarm Optimization (PSO) approach. One aspect missing from existing approaches is the capability to efficiently site and size a predefined number of DGs. Here, Hybrid Genetic-Particle Swarm Optimization aims to overcome this shortcoming. The results obtained from the proposed algorithm applied to a 45-bus radial distribution system demonstrate its good performance and capability. Results show that the HGPSO is better than PSO in order to obtain the maximum loss reduction as well as maximum voltage profile improvement for each case of optically placed multi-DGs.
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  Cite this Reference:
Arman Tarrah and Masoud Aghazadeh Mehrabani, 2013. Using Intelligent Algorithms to Find the Optimal Placement of Distributed Generation.  Research Journal of Applied Sciences, Engineering and Technology, 5(14): 3761-3766.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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