4.7 Article

Optimal allocation of distributed generators DG based Manta Ray Foraging Optimization algorithm (MRFO)

Journal

AIN SHAMS ENGINEERING JOURNAL
Volume 12, Issue 1, Pages 609-619

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ELSEVIER
DOI: 10.1016/j.asej.2020.07.009

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In this study, the Manta Ray Foraging optimization algorithm (MRFO) was applied to minimize power losses in three different networks, and the results were compared with recent applied techniques.
The endless problem of energy supplies are always floating on the surface. As a result, there are a daily improvement to optimize power generators, networks and system configuration. Renewable distributed generators (RDG) are in the heart of these developments. The size of RDG is increasing daily so, it must be optimized to maximize benefits and eliminate drawbacks. Optimization algorithms are one of the fast growing techniques. In this study the Manta Ray Foraging optimization algorithm (MRFO) is applied to minimize power losses through sizing and allocation of DG type I integrated into radial distribution network (RDN). The proposed technique was tested on three different networks, IEEE 33, 69 and 85 test systems. Also, three cases were assumed to evaluate the effectiveness of MRFO algorithm. The results were compared to recent applied techniques. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).

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