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Optimal Sizing and Sitting of Distributed Generations in Power Distribution Networks Using Firefly Algorithm

Optimal Sizing and Sitting of Distributed Generations in Power Distribution Networks Using... Compared to centralized generation, distributed generations (DGs) have numerous advantages including real power loss reduction, voltage deviation reduction, network stability enhancement, emission reduction, capacity increase of transmission lines and congestion reduction in distribution networks. Optimum placement of DGs plays a crucial role in this regard. In this paper, Firefly Algorithm (FA) was employed for sizing / sitting of various DGs in distribution networks. The aim of this paper was to minimize power loss by taking into account power factor, active power, and reactive power of DGs. Furthermore, different active and/or reactive generating/consuming DGs were also considered. The performance analysis of the proposed method was validated on standard IEEE 33- and 69-bus test systems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Technology and Economics of Smart Grids and Sustainable Energy Springer Journals

Optimal Sizing and Sitting of Distributed Generations in Power Distribution Networks Using Firefly Algorithm

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References (20)

Publisher
Springer Journals
Copyright
Copyright © Springer Nature Singapore Pte Ltd. 2020
eISSN
2199-4706
DOI
10.1007/s40866-020-00081-9
Publisher site
See Article on Publisher Site

Abstract

Compared to centralized generation, distributed generations (DGs) have numerous advantages including real power loss reduction, voltage deviation reduction, network stability enhancement, emission reduction, capacity increase of transmission lines and congestion reduction in distribution networks. Optimum placement of DGs plays a crucial role in this regard. In this paper, Firefly Algorithm (FA) was employed for sizing / sitting of various DGs in distribution networks. The aim of this paper was to minimize power loss by taking into account power factor, active power, and reactive power of DGs. Furthermore, different active and/or reactive generating/consuming DGs were also considered. The performance analysis of the proposed method was validated on standard IEEE 33- and 69-bus test systems.

Journal

Technology and Economics of Smart Grids and Sustainable EnergySpringer Journals

Published: Mar 26, 2020

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