Authors (first author is the speaker)
Due to the energy transition in Germany the energy sector is affected by massive changes that make
the planning tasks for the utilities more and more complex. Given the sharp rise in shares of non-
predictable energy supply from renewable energy sources (wind, solar) an intraday market was
established, allowing the energy suppliers to respond to changes in demand and supply situations at
very short notice. Especially the difficult predictability of renewable generation leads to imbalances
in the energy system, which cannot be covered by balancing energy mechanisms only.
Energy suppliers now have the challenge to continuously monitor their generation portfolio and
calculate forecasts for their own renewable infeed and the heat demand of their customers. In
addition, the short-term forecast of prices in the intraday market seems useful. Any new forecast
situation or any change in the conditions in the market result in a new optimization problem to
determine the optimal market behavior and to calculate the optimal operation of the power plants.
For about 20 years ProCom GmbH offers planning solutions for the energy sector, helping to optimize
energy portfolios and forecast prices, energy demand and supply. The underlying platform BoFiT
supports users starting from the model development for optimization and forecast ending at
automatically running processes for continuous trading in the energy markets. The optimization
functions are based on mixed integer programming and the forecast functions use among other
methods artificial neural networks.