Stochastic study of the connection of electric vehicles in Argentine low voltage networks

Abstract

This article proposes a multivariate probabilistic model to analyze the impact of connecting electric vehicles (EVs) to low-voltage (LV) distribution networks. The behavior of the distribution network for unmanaged charging strategies is analyzed first, taking into account different EV penetration factors on the network. The statistical variables considered were the distances traveled by the EVs, the arrival time of the EV, the state of charge (SOC), and residential demand. The methodology used included Monte-Carlo simulations. The level of technical losses, voltage at the nodes, and power flows were then analyzed. The results show that leaving the charging process in the hands of the user produces technical levels that are unacceptable for the correct grid functioning. Two possible solutions are presented in the paper to increase the level of penetration of electric vehicles while meeting the technical requirements of the grid. The first is demand management, postponing the average start time of the charging process until late at night. This method depends on the demand curve; however, our case study shows promising results because the grids are not heavily loaded at late night hours. The second solution consists of adjusting the load factor of the MV/LV transformer (and eventually the traditional radial network design) to allow for more significant EV insertion; this could be of interest in a context in which the network design is being considered. The assessment of the results provides significant information for the operators of the Argentine distribution systems (DSOs) and the regulatory authorities, in the run-up to drafting efficient and soundly based regulations for introducing this technology.