Economic Optimization of Flexible Power-Intensive Industrial Processes

BMWi Project FlexEuro

Energy generation dependent on supply – i.e. electricity production is dependent on the weather, it does not depend on the demand or the market price (e.g. wind power and photovoltaics) – has an ever increasing influence on the energy market. Especially the flexibility on the demand side is therefore an important success factor for securing our energy system in the long-term. Particularly power-intensive processes in the industry have the potential to profit economically from this.

The goal of the FlexEuro project is the development of methods and prototypes, which can be used for decisions on marketing flexibility in power consumption. To this end, we develop quantitative models and algorithms with a focus on the operational marketing of flexibility together with our project partners. In the network we work as Fraunhofer ITWM together with the University of Duisberg-Essen and two companies from stochastic optimization and industry.


Short-Term Marketing Options

The short-term marketing options for flexibility considered in the project are:

  • Reserve power markets: The reserve power guarantees the supply in case of unforeseen events in the power grid.
  • Day-ahead Auction: Trading of electricity for the following day, which takes place on EPEX Spot in Paris (Spot Market of the European Power Exchange), on EXAA in Vienna (Energy Exchange Austria) or in OTC (Over-the-Counter Trading) via OTC contracts.
  • Intraday market: Intraday trading of electricity takes place both on EPEX Spot and OTC trading, i.e. over-the-counter contracts between electricity buyers and sellers. It refers to the continuous buying and selling of electricity that is delivered on the same day.

Accurate Models and Algorithms

The different characteristics and restrictions of the markets require an individual combination of suitable financial mathematical models with optimization algorithms for each marketing option:

  • Reserve power market: market modelling and stochastic optimization of the bid
  • Day-ahead market: price forecasting and multi-criteria optimization
  • Intraday market: Stochastic modeling of the current order book and continuous generation of trading recommendations

We then bring the developed models and methods as software prototypes to the test and use them in applications of the project partners.

Project Results – Optimal Load Schedules for All Three Short-Term Markets

In the first year and a half of the project, our scientists at Fraunhofer ITWM intensively dealt with the marketing on the day-ahead market. For this purpose, we modeled the possibility of flexible consumption mathematically as a multi-criteria optimization problem. With the help of mathematical forecasts, we calculated optimal load schedules for the coming day. Through this, we showed that flexibility is economically very profitable. This is also true if the technical costs of a schedule at optimal market prices are included.

Optimal Load Schedule on the Day-Ahead Market
© Fraunhofer ITWM
Optimal Load Schedule on the Day-Ahead Market
Optimal Flexibility Distribution in Cross-Market Setting
© Fraunhofer ITWM
Optimal Flexibility Distribution in Cross-Market Setting

The goal of the second half of the project was to optimize schedules in order to expand the intraday and balancing energy market. To do this, we set up models to predict the profit in each market for a schedule. With these models, our researchers determine an optimal schedule that operates in all three short term markets considered. 

We and the project were also concerned with the price development from mid-2021, but we were still able to test the intraday algorithm live and deliver positive results. Furthermore, we proved the robustness of the developed cross-market model in a backtest during this highly volatile phase. Our analysis of the performance of the cross-market model can be found in our publication »Optimizing the Marketing of Flexibility for a Virtual Battery in Day-Ahead and Balancing Markets: A Rolling Horizon Case Study Applied Energy.«

Project Partners:

  • Fraunhofer ITWM (Project coordination of the department Financial Mathematics and cooperation in the division of Optimization)
  • University of Duisberg-Essen (Prof. Dr. Rüdiger Kiesel)
  • Decision Trees GmbH (software and consulting company with specific competence in the application of stochastic optimization in the energy industry)
  • TRIMET Aluminium (TRIMET Aluminium SE, the family business develops, produces, recycles, casts and sells modern aluminium light metal products)

Project Duration:

The project ran from September 2019 to December 2022.

The project was supported by the Federal Ministry for Economic Affairs and Energy (BMWi), to raise the associated potential for energy system transformation.

© Fraunhofer ITWM
Kick-off des Projekts war am 21. und 22.10.2019 in Essen, erst in den Räumlichkeiten der TRIMET Aluminium SE (inkl. spannender Werksführung) und am Tag drauf in den Räumlichkeiten des Projektpartners Universität Duisburg-Essen.


  1.  N. Leithäuser, T. Heller, E. Finhold, F. Schirra: »Optimal Trading of Flexible Power Consumption on the Day-Ahead Market«, Operations Research Proceedings, 2021, 2022.
  2. E. Ramentol, F. Schirra, A. Wagner: »Short- And Long-term Forecasting of Electricity Prices Using Embedding of Calendar Information in Neural Networks.«, Journal of Commodity Markets, Volume 28, 2022.
  3. C. Gärtner, E. Röger, T. Heller: »An Optimal Bidding Model to Market Flexibility on the Balancing Electricity Markets«, Energy, Volume 2004, 2022.
  4. E. Finhold, T. Heller, S.O. Krumke, N. Leithäuser: »A Bicriteria Almost Equal Minimum Cost Flow Model for Day-Ahead Trading«, Operations Research Proceedings, 2022, 2023.
  5. E. Finhold, C. Gärtner, R. Grindel, T. Heller, N. Leithäuser, E. Röger, F. Schirra: »Optimizing the Marketing of Flexibility for a Virtual Battery in Day-Ahead and Balancing Markets: A Rolling Horizon Case Study«, Journal of Commodity Markets, 2023.