University essay from Uppsala universitet/Institutionen för geovetenskaper

Abstract: With the transport sector switching to electric energy to reduce greenhouse gas emission, the supply and demand in the energy system are impacted by this transition. Meanwhile, there are not a lot of studies focus on the electrification of the vehicle fleet in Sweden. To fill up the knowledge gap, the paper aims to identify the total required electrical energy and power for the electrification of the vehicle fleet in Sweden. This includes switching passenger vehicles, light and heavy trucks, and buses to battery electric vehicles. An Electric Vehicle Power Demand Model is designed to answer the research question. It is a simplified model that can calculate energy consumption and power demand from an electric vehicle fleet. To simulate the charging schedule, four scenarios are created with differences in charge speed and the use of smart or unregulated charging. Based on the model, the electric vehicle fleet consumes 20.4 TWh of electricity per year, accounting for 14.7% of total demand in Sweden. Combing the vehicle fleet with other energy services, an average hourly peak load of 16.2 GW in summer and 24.3 in winter can be seen, while the available capacity in Sweden is around 27.1. The result indicates that the current Swedish energy system is capable of handling demand from charging the electric vehicle fleet in terms of power capacity for most times. However, undersupply may happen in some extreme condition during the winter due to higher consumption from other energy services. Furthermore, with the increasing share of renewable power in the system, the availability of these power plants can have a direct impact on the supply. This requires smart charging to shift the charging events to prevent peak hours, which can potentially decrease the peak loads up to 2 GW in EV charging demand during peak hours. However, the actual effect of it still requires more study. Lastly, the model created for the research can be used as a research or decision-making tool to estimate the impact of a group of electric vehicles in the future, therefore, contribute to the development of the sustainable energy transition.

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