All over the world, and in particular in Germany, a trend toward a more sustainable electric energy supply including energy efficiency and climate protection can be observed. Simulation models can support these energy transitions by providing beneficial insights for the development of different electricity generation mix strategies in future electric energy systems. One important input parameter for these large-scale simulations is the electricity demand, commonly obtained using empirical datasets. However, it is desirable to deploy dynamic electricity demand models to be able to investigate the behavior of the energy system under changing or specific conditions. In this paper we present such a model. We identify the most important parameters, such as the seasonality, the type of day, and the daily mean temperature to accurately model the large-scale electricity demand for Germany. We validate and implement our model in the context of a hybrid simulation framework and show its correctness and applicability.
Figure 1: Characterization of electricity demand profiles based on published data from ENTSO-E