Zusammenfassung
To investigate the effects of the future integration of electric passenger cars on the power grid, methods are needed to adequately consider this additional load in the simulation. Mainly agent-based approaches based on historic mobility data of conventional passenger cars are used in the literature to calculate a charging profile specifically for each car. Thus, the total load profile of a larger grid area has to be estimated in a bottom-up process considering a high number of individual charging profiles, which can be complex and time consuming. In contrast, this paper presents a new top-down approach, in which the total energy demand expected from the electric passenger cars is first determined based on their assumed mileage, their temperature dependent consumption as well the charging efficiency. This resulting total energy demand is then split up into different charging location types. The proposed method includes charging at home, in public and at the workplace. Furthermore, standard load profiles for each charging location type are derived based on real usage data. These can then be scaled based on energy demand, which may be dependent on the degree of electrification and other factors. The presented approach is characterized by a high computing efficiency, since there is no need for the generation of a high amount of individual charging profiles. This is shown in an exemplary case study that examines the impact of electric passenger cars within the state of Baden-Wuerttemberg, Germany.
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