Teaching

Courses

The Energy&IT group participates as teaching staff in the following courses:

384.141, Fachvertiefung – Softwareentwicklung VU, 2021W, 4.0h, 5.0EC

384.146, Smart Grids VO, 2021W, 2.0h, 3.0EC

384.171, Sensornetzwerke PR, 2021W, 4.0h, 6.0EC

384.173, Mikrocomputer VU, 2021W, 3.0h, 4.0EC

370.038, Labor Smart Grids UE, 2021S, 2.0h, 3.0EC

384.061, Objektorientiertes Programmieren VU, 2021S, 2.0h, 3.0EC

384.139, Fachvertiefung – Computersysteme VU, 2021S, 4.0h, 5.0EC

Open Thesis Topics

The Energy&IT group offers theses in the domains of Smart Grid, Automation/Industry and Artificial Intelligence to excellent bachelor and master students. If you are interested, please contact the Energy&IT group.

Supervised Theses

The following bachelor and master theses were supervised by Energy&IT group members (uncomplete list):

“Pattern recognition in a heterogeneous smart grid environment” by Matthias Bittner (2021)

“Implementation of a multi-band RTK receiver system with Arduino” by Edwin Willegger (2020)

“Automation of Hardware/Software Integration Tests on Mikrocontroller Target Environments” by Florian Muttenthaler (2020)

“Evaluation of Methods for Measuring the Energy Efficiency of Video Game Console Products” by Cevdet Kilic (2020)

“Solutions for automation of LV-substations in a G3-PLC network” by Behzad Parvin (2020)

“Sustainability of videogames consoles – thermal/electrical analysis and evaluation” by Thomas Leopold (2020)

“Proof-of-concept for a smart grid controller blockchain platform for virtual power plants” by Andrija Goranovic (2019)

“Distributed optimization in electrical grids – simulation and validation” by Clemens Korner (2019)

“Energy harvesting and power measurement in distribution substations using a current transformer” by Daniel Hauer (2017)