Student (f/m/x) Master's thesis: Forecasting day-ahead and intraday electricity market results (Oldenburg) na Deutsches Zentrum für Luft- und Raumfahrt

At the Institute of Networked Energy Systems, we pursue an overarching goal: we want to make energy transition in the economy and society successful through our research. With about 190 employees at our Oldenburg and Stuttgart sites, we develop transformation strategies and technical solutions to efficiently link the electricity, heating, transport and industrial sectors at all levels of the energy system in a way that benefits the system. To this end, we work together with our partners from industry and research to develop a holistic understanding of the system and effective system solutions.

Would you like to work in an interactive, co-operative and international team? Are you interested in the new and further development of renewable energy technologies, in particular decentralised energy supply and its flexibility? Then the Institute of Networked Energy Systems is an attractive employer for you.

What awaits you

The Energy System Technology department focuses on the interaction between system-relevant energy technologies within decentralised networked structures. In the distribution grid in particular, we are striving for new architectures for the energy systems of the future that ensure robust grid operation even under the influence of renewable energy sources.

The Energy Management research group develops methods and strategies to optimise the operation and design of future energy systems hand in hand.

The DECENT project is working on concepts and solutions with which decentralised flexibility potentials and system-friendly behaviour can be quantified and upgraded and how this flexibility can participate in the energy market.

Your tasks

• You will develop forecasting methods for day-ahead and intraday market results based on probabilistic methods and/or AI algorithms.

• You will evaluate the quality of the forecasting methods developed.

• You use the forecasts in a use case for the optimisation of heat generation

  using combined heat and power plants.

   

What you bring with you

• You already have some basic knowledge of energy systems, especially power generation.
• You already have a very good command of German and English.

• You already have some experience with data science methods, preferably time series forecasting with machine learning and probabilistic forecasting methods.

• You are already familiar with programming tasks, especially with Python.

 We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 2940) please contact:

Dr Sunke Schlüters
Tel.: 0441 99906295