Henrik Wagner, Sarah Eckhoff, Sarah Fayed, Fernando Peñaherrera V., Annika Ofenloch, Oliver Werth, Bernd Engel, Michael H. Breitner, Sebastian Lehnhoff, and Johannes Rolink
The demand for charging facilities is growing in parallel to the number of electric vehicles (EV). This demand will be predominantly covered by private charging points connected to the low-voltage grid . The increased load resulting from these charging processes may cause grid instabilities depending on operational factors, e.g. simultaneity factor and penetration rate. These high load cases were unknown while planning and building the grid of existing districts. Therefore, critical grid situations resulting from high penetration rates of EV can occur. The goal of this research is to analyze the effects of an increasing EV penetration rate in existing districts with opportunities for different levels of cooperative energy generation and to determine the maximum possible grid capacity for EV charging. Identified limiting factors are then considered in further simulations regarding the energy refurbishment of the district trying to enhance the grid’s capacity for EV. Thus, the influence of different technologies for cooperative energy generation, e.g. photovoltaic systems, on the grid’s capacity can be determined. The simulations will consider a district in Lower Saxony, Northern Germany, mainly consisting of public housing with currently no installed energy generation plants or charging infrastructure. Due to the diverse nature of the components involved in the simulation of this system, the co-simulation framework mosaik is required to conduct the power system analyses. Mosaik allows coupling different modeling tools and enables orchestration and communication of parameters between components so that a systems-wide perspective is achieved. In the context of the co-simulation, emobpy, an open-source tool for calculating the grid electricity demand of EV from empirical data, is coupled with pandapower, an open-source tool for power system modeling to determine the grid capacity for EV. The EV model provides time-dependent power values of the charging processes occurring in the district. The user-specific behavior (mobility behavior, charging frequency, charging times), current and future penetration rates, and simultaneity factors are considered. For a future scenario, photovoltaic and battery storage models are added and coupled to the energy system to increase the grid’s capacity for EV. The researchers of the underlying research project “Zukunftslabor Energie” (Future Laboratory “Digitalization Energy”) commit their research activities to the standards of Open Science. The simulation scenario, the existing models and the newly developed or modified models will be accessible under an open-source license, enabling a transparent research process and improving the research quality as well as accessibility. Based on the developed co-simulation, further case studies on the mentioned and other districts could be subsequently investigated, allowing a modular extension.