Machine Learning for Renewable Energy Systems

We’re again offering the Seminar on Machine Learning for Renewable Energy Systems in the Summer Term 2023.

General

The seminar starts with introductory lectures, followed by an individual working phase and presentations at the end of the 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 present a recent paper addressing challenges in renewable energy systems with machine learning or be able to implement a machine learning approach to address a challenge in renewable energy systems.

There’ll be two options this term. You can either present a paper that applies ML to a problem related to renewable energy systems, or write code implementing a given ML approach to data from renewable energy systems.

What you’ll have to do

Paper track:

• write a seminar paper reviewing a recent paper that applies machine learning to renewable energy systems (ca. 5 pages)
• give a presentation (15 min)
• review paper from fellow students (peer review)

Coding track:

• implement a ML method on given energy data and make code publicly available
• write documentation of the code and results
• review documentation/code from fellow students (peer review)

Organisation and Evaluation

Credits: 3 ECTS

Language: English

Dates & Room: Wednesdays, 12 - 2pm, Seminar Room 4th floor, AI Research Building (Maria-von-Linden Str 6)

Only the final seminar paper/ documentation (50%) and the presentation/ code (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.

Registration

If you want to participate in the course, please register via ILIAS , the registration starts on March, 30. The course is limited on a first come first serve basis, please indicate whether you want to present a paper or write code when registering.

Tentative Course Plan