• EN
  • 3 questions for …

    Tobias Pfingsten

    As the share of green energies grows, fluctuations in the power grids also increase, because wind and sun are not available as a reliable source of energy around the clock. In collaboration with the Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), STEAG's Trading business unit has developed an approach that can be used to bundle and efficiently optimize decentralized green power generation portfolios and storage systems.

    Tobias Pfingsten (45) heads the Quantitative Methods & Trading Systems department in STEAG's Trading division. He studied physics and completed his doctorate on the subject of machine learning at the Max Planck Institute for Intelligent Systems in Tübingen. He has been working in the energy sector for more than 15 years, among others for RWE and the Boston Consulting Group. Since 2018, Tobias Pfingsten has been in the service of STEAG, where he is responsible in particular for the further development of systems and models for trading and plant optimization.

    How did the collaboration between STEAG and SCAI and the joint solution that is now available come about?
    SCAI has a high level of expertise, particularly in the optimization of energy systems and artificial intelligence. In addition, we have already had good experience of cooperation in the past.

    What advantages does the approach developed by STEAG and SCAI offer customers?
    Our most important concern was to create a solution with which our Trading business unit can optimally manage decentralized assets. The prerequisite for this is that, on the one hand, the specific technical framework conditions at the respective customer are met. At the same time, however, our trading specialists must be able to optimally manage a large number of diverse assets.

    One example of this is the optimization of local combined heat and power plants in conjunction with heat storage facilities depending on the current demand for heat and electricity.

    The advantage of our solution is its modular structure. This allows us to respond quickly to market changes and new customer requirements and to adapt our operational processes accordingly.

    Of particular interest to customers is the fact that our solution uses artificial intelligence (AI) to enable further optimization even in the face of high market uncertainty.

    Can you already identify any trends with regard to the further development of the market and portfolio management systems?
    Of course, everyone is talking about AI at the moment. From our point of view, such approaches will not replace classical optimization, but they can offer a good supplement, especially in electricity trading.