Machine Learning for Renewable Energy Systems

We’re offering the Seminar on Machine Learning for Renewable Energy Systems in the Summer Term 2024.


The seminar starts with introductory lectures, followed by an individual working phase and presentations in the second half of term.

The aim is that at the end of the course, you will:

  • Understand the basics of renewable energy systems and the role machine learning can play to control, optimise, and understand them.
  • Be able to identify current challenges in renewable energy systems.
  • Be able to discuss machine learning approaches that address these challenges.
  • Be able to implement and present a machine learning approach to address a challenge in renewable energy systems.

What you’ll have to do

  • implement a ML method on given energy data and make code publicly available
  • present the method and results in a short presentation (12 min)
  • write a short paper about your approach (max 5 pages)
  • review papers from fellow students (peer review)

Organisation and Evaluation

Credits: 3 ECTS

Language: English

Dates & Room: Tuesdays, 10 - 12noon, Lecture Hall, AI Research Building (Maria-von-Linden Str 6), Seminar starts in the second week of term.

Only the final seminar paper (50%) and the presentation (50%) are graded. The reviews and first version of the paper have to be handed-in on time to pass the course. Preliminary deadlines can be found at the bottom of this page in the tentative course plan.


If you want to participate in the course, please register via Moodle, the registration starts on March, 29th. The course is limited to 15 participants.

Tentative Course Plan

23.4.Overview of the Seminar & Introduction to Renewable Energy Systems
30.4.Markets, Energy System Modelling, Climate Change Impacts and Sustainable ML
07.5.Data and Task Discussion & Academic Writing and Reviewing
08.5. - 24.6.Individual Working Phase
24.6.Deadline First Hand-in Seminar Paper
25.6.Presentations and Discussion
02.7.Presentations and Discussion
09.7.Presentations and Discussion
16.7.Deadline Reviews
23.8.Deadline Revised Seminar Paper