We offer an exiting

Master Thesis - Reinforcement Learning for Industrial Demand Response


At the Institute of Energy and Climate Research - Energy Systems Engineering (IEK-10) we focus on the optimal design and operation of integrated, decentralized energy systems with a high share of renewable energy. Computer simulation and numerical optimization are our essential tools to arrive at efficient, reliable, and cost-effective solutions. We contribute both to the development of mathematical models and to the development of improved simulation methods and optimization algorithms. Our methods and software-tools are validated against operating data of real systems. Furthermore, we conduct comprehensive case studies in order to test and further improve the scalability and the performance of our models and algorithms. Specially adapted methods and codes enable us to exploit the potential of high-performance computing with the aim of solving particularly large and complex problems.

Institute issuing the offer
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Your Job:

The increasing share of intermittent renewable energy sources leads to new challenges and opportunities in the operation of energy systems. Nowadays, electricity prices can rise and fall by an order of magnitude within one day. Thus power grid customers have an incentive to shift production in order to benefit from intervals with low prices. To enable load-shifting for processes with nonlinear dynamics and constraints on states, sophisticated control methods are needed. Using deep reinforcement learning (RL), complex control policies can be learned, but this requires large amounts of data and thus many interactions with the environment.

Your task for this thesis will be to implement a specialized deep RL algorithm for industrial demand response applications and compare its performance to standard state-of-the-art RL-algorithms.

Your Profile:

  • Current master studies in engineering, computer science, simulation science, data science or a comparable field of study
  • Good programming skills in Python
  • Ideally experience in a major deep learning framework such as PyTorch
  • Interest in deep reinforcement learning
  • Fluent in English or German (spoken and written)
  • Independent working style and good analytical skills
  • Willingness to familiarise yourself with new methods

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with:

  • Intensive supervision (if desired) by experienced academic colleagues
  • Excellent opportunities for home office
  • A large research campus with green spaces, offering the best possible means for networking with colleagues and pursuing sports alongside work
  • An interesting and socially relevant topic for your thesis with future-oriented themes
  • Ideal conditions for gaining practical experience alongside your studies
  • An interdisciplinary collaboration on projects in an international, committed and collegial team
  • Excellent technical equipment and the newest technology
  • Qualified support through your scientific colleagues
  • The chance to independently prepare and work on your tasks
  • Reasonable remuneration, if work is done (partially) in our office in Jülich

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.

We look forward to receiving your application. The job will be advertised until the position has been successfully filled. You should therefore submit your application as soon as possible.

Apply now

Questions about the offer?

Please feel free to contact us via our contact form.
Please note that for technical reasons we cannot accept applications by e-mail.

Last Modified: 16.11.2022