The ENets project team creates mathematical forecast models of how demand for electricity will develop over the course of the year in order to optimally design the power grid of the future. In the BMBF project, four scientific partners are working together with four partners from industry.
Renewable energies now cover 36 percent of the electricity supply (as of December 2017) and have already covered Germany's entire electricity requirements in just a few hours. The gradual conversion from coal and nuclear power to solar, wind and biomass will bring about changes for industry and consumers. Renewable energies are volatile and the supply fluctuates depending on the strength of wind and sun. In order to avoid purchases from abroad on peak days and to ensure security of supply, forecasting models help to determine how demand develops over the course of the year.
The core of our research project is to create a model to describe the electricity grid and to forecast feed-in and offtake. At the end of the project, an algorithmically efficient overall model is to be created that offers a coupled perspective of market and network as well as of electricity and gas - levels that have so far mostly been analyzed separately.
We Deal With the Following Questions:
Development of models and algorithms for the integration of stochastic input variables into the physical network models for electricity and gas
Integration of price-sensitive demand (smart-grids) and volatile producers (renewable energies) in electricity market models for the day-ahead and intraday market
Methods for coupling and operational optimization of the electricity and gas network under consideration of uncertain input variables