The concept of electrical-mobility is becoming even more attracting worldwide and Fast Charging Stations (FCSs) will start appearing in the near future directly connected to MV networks. Consequently, a correct expansion plan of the electric distribution system cannot pass over the knowledge or the prediction of the consumption of this new load. In the paper, daily demand profiles of the FCS, modelled by the authors in a previous work, are used in a new planning tool to find the optimal allocation of public fast charging stations in a given network structure. The tool applies an evolutionary Multi-Objective philosophy, based on the Non-dominated Sorting Genetic Algorithm-II, in order to minimize the negative effects of concentrated and intense absorptions of power in the FCSs across the distribution network without penalizing their diffusion in the urban texture.
Planning of fast charging station placement
CELLI, GIANNI;MOCCI, SUSANNA;PILO, FABRIZIO GIULIO LUCA;SOMA, GIAN GIUSEPPE
2014-01-01
Abstract
The concept of electrical-mobility is becoming even more attracting worldwide and Fast Charging Stations (FCSs) will start appearing in the near future directly connected to MV networks. Consequently, a correct expansion plan of the electric distribution system cannot pass over the knowledge or the prediction of the consumption of this new load. In the paper, daily demand profiles of the FCS, modelled by the authors in a previous work, are used in a new planning tool to find the optimal allocation of public fast charging stations in a given network structure. The tool applies an evolutionary Multi-Objective philosophy, based on the Non-dominated Sorting Genetic Algorithm-II, in order to minimize the negative effects of concentrated and intense absorptions of power in the FCSs across the distribution network without penalizing their diffusion in the urban texture.
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