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