Forecast methods for investment of country wide electric vehicle charging stations: Lithuanian case

Abstract

The aim of this article is to present a complex model for forecasting the required investments based on the forecast of the increase in the number of electric vehicles and their demand for energy and investments. Scientific problem is that current approach on forecasting of electric vehicles is to abstract, forecast models can’t be transferred from country to country. This article proposes a model of forecasting investments based on the forecast of the increase in the number of electric vehicles and their demand on energy. The findings of the Lithuanian case analysis, which is expressed in three scenarios, focuses on two trends. The most promising scenario projects 319 470 electric vehicles by 2030 which will demand for 1.09 TWh of electricity, representing 8.4–9.9 percent of the total energy consumption in the country. It demands EUR 230.0 million in the low-voltage grid and EUR 209.0 million in the charging stations. Main limitations are related to statistics available for modelling and human behaviour uncertainty, especially in evaluation impact of measures to foster use of electric vehicles.