Electric Vehicle Load Impact on 400 V Distribution System: Monte Carlo Simulation
Author: Róbert B. Ólafsson
Advisors: Laurentiu Anton, Kári Hreinsson
Published in: Skemman (Library of Research Publications in Iceland)
Accepted on: January 25, 2021
Abstract
The Icelandic government adopted the Paris Agreement pledge to undertake aggressive efforts to combat climate change and reduce greenhouse gas emissions. The energy transition of the transportation system has been identified as one of the primary methods to achieve the targets of the Paris Agreement. The transition from internal combustion engine vehicles to electric vehicles (EV) or plug-in hybrid vehicles has already started. The increase of EV sales in Iceland is expanding rapidly as the Icelandic government is incentivizing consumers to choose clean energy vehicles by offering subsidies. The impact of EV charging loads on electric distribution systems will escalate as the amount of EVs increases. In 2018, Samorka, the association of energy and utility companies, launched a research study to collect data and analyze the driving- and charging behavior of EVs in Iceland. One of the key purposes of the study for distribution utility companies was to determine whether the system in its current state could withstand increased stresses brought on by EV charging within the system.
In this thesis, the impact of an added EV charging load on one specific distribution substation system within the greater capital area was simulated and analyzed. The objective was to pinpoint any weaknesses in the system and determine at which point the system became overloaded with respect to the line thermal limitations and the voltage regulation limits. This was achieved by analyzing data from the Samorka electric vehicle research study and subsequently modeling an EV charging load profile. A load profile for the residential households within the distribution substation system was also generated. The EV charging load profile was generated for each EV type and five specifically defined seasonal categories. Pandapower data analysis software and power flow solver was used to compute the power flow of the distribution substation system. The Monte Carlo simulation method was then used to predict the probability for variation of outcomes.
The study concludes that this particular distribution substation system is sufficiently robust to handle the added EV load, performing above initial expectations. As increasing amounts of EVs were added to the system, critical limits of the system were breached and the most vulnerable branch of the system was identified. The voltage drop limit was breached most frequently and was therefore concluded to be the most likely limit to breached with increasing EV charging loads on the system.
