Probabilistic Assessment of Electric Vehicle Impact on Distribution Network of Surabaya, Indonesia

Abstract

This paper investigates the impacts of increasing levels of electric vehicle (EV) penetration in an urban distribution network of Surabaya, Indonesia. Surabaya is the second most populous city in Indonesia where the network is operated by national electric company of Indonesia (PT PLN Disjatim) The investigation is conducted under concentrated and distributed EV penetration (each with 10% and 20% penetration calculated as a percentage of residential load). Loads are modeled as dependent variable of the hour selection within the day and added with a normally distributed uncertainty on each of selected load value to better replicate uncertainty within the daily loading. Whereas, EV charging pattern is modelled as probabilistic uncertain sources using Markov Chain Monte Carlo to better replicate the practical condition. Voltage at each node and aggregate losses are employed to quantify and contextualize the impact. Maximum EV penetration where it violates the statutory threshold is also explored in this paper. Simulation result shows that Surabaya distribution network able to withstand EV penetration in both scenarios with the maximum EV penetration is almost doubled than the highest penetration level from simulated cases.