Despite ambitious climate goals, the German transportation sector has failed to reduce emissions. As these emissions are dominated by personal vehicles, electric vehicles are central for achieving environmental objectives. To determine potential emission reductions from electric vehicles, a detailed analysis of the transportation and energy sectors is necessary. Thus we present a methodology to calculate charging demand of electric vehicles using a time and location specific microsimulation and probability estimation based on a utility function for charging behavior. The transportation model is coupled with a detailed energy model for Germany, which provides electricity generation per energy source on an hourly basis over a year. We apply the methodology and models to the case study of Germany in 2030 for five scenarios. The scenarios represent difference pricing schemes reflecting policy options for electric vehicles. The results show that charging demand can be shifted using market incentives. We find that charging subsidies can shift charging demand to or away from peaks. We then combine charging demand with the energy model to quantify the CO2 emissions. The results show that shifting charging demand can reduce emissions, albeit at a minimal level. For the entire year, shifting charging to the daytime can reduce emissions by 2%. New areas of research including bidirectional charging and hourly pricing are needed to ensure maximum emission reductions from electric vehicles.