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Supervision Strategy to Mitigate the Effect of Electric Vehicles (EVs) Charging Load on Power Distribution System Operations


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DOI: https://doi.org/10.15866/irecon.v6i6.15986

Abstract


In a fast charging station (FCS) electrical energy is supplied to rapidly charge electric vehicles (EVs). EV charging station acts as the load of the power distribution system, and the large-sized charging activity may bring an effect on the power distribution system. In this paper, an approach to forecast the characteristic of power consumption due to EVs charging has been studied by using Monte Carlo and Artificial Neural Network (ANN) method. The traveling distance of EV users, the state of charge (SOC) of EV battery, and the arrival time to the FCS have been considered in this study. The proposed mathematical equation has been used to determine the number of FCS in the area. Finally, a Fuzzy supervisor design methodology has been applied to model supervision strategy in order to reduce the effect on the power distribution system by considering the electric energy demand of EV and number of EV to be charged. Thus, the obtained results indicate that the effect of EVs charging on the power distribution system increases voltage fluctuation and power losses. A supervision strategy can mitigate the effect of EVs charging on the power distribution system.
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Keywords


Monte Carlo; Artificial Neural Network; Fuzzy Supervisor Design Methodology; Fast Charging Station; State of Charge

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References


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