Lectures about Machine Learning in Power Systems

Machine Learning for Power Systems. Inaugural Adelaide Power Systems Summer School 2020 (Australia).

The most complete set of material, videos, and slides. (Summer School Website)

Machine Learning for Power Systems: Physics-Informed Neural Networks and Verification. IEEE PES Big Data Analytics Webinar, April 2020.

Interested in removing barriers for Machine Learning Applications in Power Systems? This is the lecture for that! A more complete version of this material is also provided in the Lecture Videos for the Adelaide Summer School above.

Data-Driven applications for Power System Security Assessment. DTU Summer School 2019.

From Decision Trees and Neural Networks to MILP: Power System Optimization Considering Dynamic Stability Constraints. European Control Conference Workshop, May 2020.

Efficient Creation of Datasets for Data-Driven Power System Applications Power System Computation Conference (PSCC), June 2020.

Teaching at DTU


2018-Current

31765: Optimization in Modern Power Systems

Fall Semester, 5 ECTS. The course takes place every Tuesday morning 8am-12pm during the 13-week period of the semester.

31765: Lecture Slides and Course Material

31765: Lecture Notes on Optimal Power Flow (constantly updating) (new chapters to be added)

Videos of relevant lectures from the DTU CEE Summer School 2018


31730: Fundamentals of Electric Power Engineering

Fall Semester 2018, 10 ECTS. The course takes place every Tuesday afternoon 13pm-17pm and every Friday morning 8am-12am during the 13-week period of the semester.

31730: Lecture Slides and Course Description for 2018





2017-2018

31765: Optimization in Modern Power Systems

31730: Fundamentals of Electric Power Engineering


2016-2017

Optimization in Modern Power Systems

31730: Fundamentals of Electric Power Engineering