Monte Carlo simulation of electric vehicle loads respect to return home from work and impacts to the low voltage side of distribution network

Abstract

Usage of electrical vehicles (EV) is increasing at high rate due to their great benefits to the community well-being. However, EVs have considerable impacts to electrical power networks and especially to the low voltage side of the distribution network. In order to determine the impacts of EVs accurately, uncertain behaviors of drivers were modeled using Monte Carlo simulations. This method is proven to be a robust tool for the evaluation of stochastic processes and getting deterministic results out of it. Furthermore, real-world traffic pattern data were used to model drivers’ behaviors. Return home time of EVs was used as a charging start time, and average commute distance of drivers was used to determine the charging duration. Also, residential area was taken as a pilot network. Hourly basis transformer loading data were obtained and used to realistically reflect the base load of the pilot network. Load flow analysis was performed for non-EV and with-EVs scenarios. The results of the analysis were represented in a probabilistic approach. Violations of results were investigated according to power quality limits. Consequently, impacts of the EV charging load to the low voltage side of distribution network were analyzed in terms of voltage drops, transformers’ loadings, power losses and voltage unbalance. This study showed that with a 50% penetration rate of EVs, the probability of voltage violation increases by approximately 25%.