The transformation of energy systems in Germany, Europe and worldwide is one of the major challenges of the 21st century. In the coming decades, this process will lead to developments that cannot be predicted today. Modeling scenarios that take into account both the complexity of the energy system and the uncertainties regarding future developments is an important task for science. In principle, a large number of different simulation and optimization models with different temporal resolutions are available for creating scenarios. A complete picture of the energy system can often only be achieved by model coupling, in which models that focus on the overall energy picture but usually have a low temporal resolution (e.g. energy system models) are linked to models with finer time steps (e.g. electricity market or grid models) that focus on subsystems. The data-side coupling of the different model types has often been done by using standard load curves. Accordingly, the load profile was only adjusted in level. While this approach is useful for present analyses and short-term scenario analyses, there is a risk of erroneous results for long-term scenario analyses, since the approach implies that the shape of today's load curve will remain constant in the future. Structural effects due to the implementation of new technologies (e.g., e-mobility, electricity storage, technologies in the field of digitalization) and due to societal change (e.g., trend toward digitalization, increased use of home office, changed opening hours, driving bans) have often been ignored in the past. The approaches available to date have been largely limited to changes resulting from the implementation of new technologies that serve to manage electricity supply and demand (e.g., smart grid). The effects of societal change on electricity demand or its level and temporal structure have not been explicitly investigated so far. Accordingly, existing uncertainties regarding the development of electricity demand and its importance for the energy transition have also been largely underestimated or neglected so far. It is already apparent that the energy transition is reaching its limits not in terms of quantity, but in terms of capacity, and that the simultaneous consideration of work and power, including demand-based flexibility, is becoming increasingly important.
Aims and Approach
The aim of this project is to illuminate this blind spot in energy system research and to generate precisely fitting load curves for specific combinations of technology development and societal development in level and profile. For this purpose, an open source demand tool will be developed by, on the one hand, storing the corresponding combinations with their specific demand for energy services and, on the other hand, providing an interface between energy system models (ESM) and electricity market models (SMM). The usability of the demand tool is tested exemplarily in the project. Due to the free availability of the demand tool, which is explicitly not exclusively designed for the models used in the project, but should be generically applicable, it is intended to enable other users of ESM or SMM to directly integrate the project results into their modeling. In addition, the exemplary application of the demand tool is intended to provide an indication of the extent to which societal change affects issues around the technology mix, security of supply, and affordability of the energy transition.
ZIRIUS has the overall project management and is mainly responsible for the work packages 1 "Defining megatrend as well as demand-impacting societal aspects and their impact on energy services", 2 "Creating consistent sector-specific driver constellations for the load profile change with the Cross-Impact Balance Analysis (CIB)", 3 "Creating consistent cross-sectoral driver constellations for load profile change with cross-impact balance analysis (CIB)" and 8 "Reflection and dissemination" as well as involved in work packages 4 "Developing hypotheses on variant combinations with load profile-effective changes and their quantitative implementation" and 5 "Energy system modeling".