The goal of this work is to evaluate the impact of the e-mobility charging processes on the electric grid, in a real-life study case. An effective approach is proposed to study the increase in the energy consumption on the grid with respect to both grid operation and efficiency. The work is developed considering three different recharging technologies, slow (based on domestic users), fast (based on public charging stations), and very fast (based on enhanced public charging stations). Furthermore, three different technologies distributions are evaluated (e.g. different scenarios on charging station deployment are simulated). The results show that fast charging technologies could better fit with e.cars exploitment, but they could cause also a significant stress increase over the grid. The paper is devoted to quantify such effects.

Monte Carlo Procedure to Evaluate the E-mobility Impact on the Electric Distribution Grid

BOVERA, FILIPPO;Falabretti, D.;Moncecchi, M.;Delfanti, M.;Merlo, M.
2018-01-01

Abstract

The goal of this work is to evaluate the impact of the e-mobility charging processes on the electric grid, in a real-life study case. An effective approach is proposed to study the increase in the energy consumption on the grid with respect to both grid operation and efficiency. The work is developed considering three different recharging technologies, slow (based on domestic users), fast (based on public charging stations), and very fast (based on enhanced public charging stations). Furthermore, three different technologies distributions are evaluated (e.g. different scenarios on charging station deployment are simulated). The results show that fast charging technologies could better fit with e.cars exploitment, but they could cause also a significant stress increase over the grid. The paper is devoted to quantify such effects.
2018
2018 International Conference of Electrical and Electronic Technologies for Automotive, AUTOMOTIVE 2018
9788887237382
e-mobility; hosting capacity; inteGRIDy; Monte Carlo; San Severino Marche; Control and Optimization; Automotive Engineering; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1070448
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