The effects of rental electric vehicles on fast charging demand

Abstract

Accurately forecasting charging demand is a major factor in energy providers’ ability to meet said demand. A number of methods have been proposed in the literature. This master thesis aims to provide a framework for energy providers to forecast charging demand due to increased EV adoption. Specifically, this research examines the effects that rental EV adoption has on charging demand at Icelandic energy provider ON Power’s fast charging stations. Further, it establishes how increased technological developments and infrastructure spending can be balanced to avoid unnecessary costs, and if ON Power’s charging infrastructure is prepared to meet the electricity demand that a fully electrified rental car fleet would bring. To answer these questions, an agent-based modeling framework was constructed to simulate charging demand in ON Power’s network. The model simulates all tourists that use rental cars in driving the Icelandic ring road as if the entire fleet consisted of EVs. A case study is conducted where the Icelandic ring road is split into nine zones, and six scenarios that each reflect different technological developments are simulated using the modeling framework. The research findings indicate a significant change in charging demand. Firstly, rental EVs affect seasonal charging demand with more than half of the demand occurring in the summer months of June-August. Secondly, geographical charging demand shifts from mostly being in the greater capital area, to mostly being outside of it. Thirdly, a sufficient charging infrastructure at Keflavík Airport is a major factor in the electrification of the Icelandic rental car fleet. The research findings further indicate that with the right strategy, it is well within reach for ON Power to handle the rental EV charging demand. A strategy is proposed for ON power to avoid unnecessary spending while still meeting charging demand, which considers current demand, future demand, and how new charging station locations should be determined.