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.

Intermediate Score at the Half

In the first one and a half years, our scientists at the ITWM dealt intensively with the marketing on the day-ahead market. For this purpose, the possibility of flexible consumption was modeled mathematically as a multi-criteria optimization problem. Mathematical forecasts were then used to calculate optimal load schedules for the coming day. Here we were able to show that flexibility is economically very profitable. This is also true when the technical costs of a schedule at optimal market prices are included.

In parallel, we started to look at the marketing possibilities of flexibility in the intraday market. For this purpose, order book data, which provide a history of past buy and sell bids, were processed and analyzed. Again, there is great potential for marketing flexibility. Work on a prototype that will help the project partners to make practical use of the potential can begin soon.

Zusammenarbeit unter Pandemiebedingungen
© Fraunhofer ITWM
Auch während der Pandemie gab es einen regen Austausch zwischen den Projektpartnern. Zusätzlich zum monatlichen Austausch fand vom 20.04.2021 bis 22.04.2021 bereits das dritte Halbjahrestreffen rein virtuell statt bei dem die Teilnehmenden ihre Ergebnisse vorstellten.
Kick-off-Meeting
© 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.

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 will run from September 2019 to December 2022.

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

BMWi
© BMWi