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Optimal Siting and Sizing of DGs on Distribution Networks Using Grey Wolf Algorithm


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DOI: https://doi.org/10.15866/irecon.v9i3.20365

Abstract


The penetration of renewable energy resources in power system as a distribution generations (DGs) is increasing due to the continuous increase in the electric energy demands and the fluctuations of fossil fuel prices, creating many economic challenges including shortages in the electricity and water resources. In order to overcome these challenges, there has been a great revolution in using DGs in distribution networks to improve the voltage profile and the power quality of the network. On the other hand, DGs contribute in increasing the generation capacity of the network, which helps to overcome the increase in the electric energy demand problem. This study shows the differences between two methods for optimizing operations, Grey wolf optimizer (GWO) and Genetic Algorithm (GA), in order to obtain the ideal and best capacity value, number and locations of the DGs. In this paper, the distribution radial networks used to apply the GWO and GA are IEEE33 bus and IEEE69 bus systems. The comparison has showed the greatness and the more successful results of the GWO than the ones of the GA and the disadvantages of GWO compared to the old GA results.
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Keywords


Grey Wolf Optimizer (GWO); Distribution Generation (DG); Voltage Profile; Power Losses; Genetic Algorithm (GA); Heuristic Algorithm; Metaheuristics

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References


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