Using Open Data for Modeling and Simulation of the All Electrical Society in eASiMOV

The present study examines a future energy systems scenario, the so-called All Electrical Society (AES), which is defined by a very high number of active prosumers in the distribution grid in view of future 100% renewables-based energy systems. In this paper, we present data modeling methods that describe the power consumption behavior and power generation patterns via time series for 78 prosumers, each fully equipped with rooftop PV, two battery electrical vehicles and a heat pump. Quasi-dynamic simulations of a low voltage grid under stress conditions are performed using open data and free software. The simulatively determined increase in network utilization and congestion is also compared with the currently available grid capacity gained through extensive measurements in the examined distribution grid. The result is that in the AES scenario the current deployed electrical infrastructure of the distribution grid will be more than heavily overloaded, both the transformers and the respective power lines