Charging for Reduced Climate Emissions and a Living countryside

Abstract: The purpose of this project is to create a map showcasing the distribution of charging stations in the surrounding areas of Uppsala city in Uppsala Municipality. Additionally, the project examines the expected development of electric car utilization, identifies essential requirements, and highlights significant actors driving this development. Through an analysis of factors, such as demographic data, geographical data, car fleet data, car density and travel patterns, the project seeks to gain insight into the present and future usage patterns of electric cars. By understanding these factors, the research contributes to a better understanding of the dynamics surrounding the adoption of electric cars outside cities. Moreover, this project provides information on the optimal placement of charging infrastructure to facilitate the transition towards electric mobility. Calculations and assumptions are made to calculate the total number of electric cars in Uppsala city's surrounding areas in 2040. Based on this number, the total installed public power capacity needed is calculated in accordance with an EU regulation called AFIR. The total capacity is distributed on five different power capacities to match the need at each location. To achieve this, key actors have been examined. In addition, development and key actors in Norway are analyzed to examine similarities and to give a brief view into the future.  The results indicate that there will be a significant increase of electric cars in Uppsala Municipality. Therefore, expanding the charging infrastructure is shown to be essential. Due to the expected high usage of home charging outside cities, public charging is believed to be mostly necessary for tourists and passersby. Nevertheless, there are uncertainties that could influence the development of electric cars, which in turn would have an impact on the results. Finally, there follows a discussion both on the results and factors which could have affected the model.