Lecture slides for the current lecture will be posted at least one hour prior to that class. Videos will be posted within one day of the end of lecture.
Lecture Slides:
- Intro (updated 8/27/13)
- ML 1: Linear regression (updated 9/10/13)
- Linear algebra review
- MATLAB review script file
- ML 2: Nonlinear regression
- ML 3: Classification
- ML 4: Evaluation
- EPS 1: DC and AC Circuits
- EPS 2: Generators, Three Phase Power, and Power Electronics
- EPS 3: Power Flow and Markets
- Control 1: Introduction
- Control 2: Dynamical Systems
- Control 3: Control of Dynamical Systems
- Control 4: Stochastic Control
- Future Directions in Smart Grid Research
Lecture Videos:
- Lecture 1: Introduction (slides)
- Lecture 2: Energy and Linear Regression (slides)
- Lecture 3: Linear regression (cont), linear algebra review (slides)
- Lecture 4: Linear algebra (cont), matrix calculus, MATLAB (slides)
- Lecture 5: MATLAB (cont), optimization, alternative losses (slides)
- Lecture 6: Nonlinear regression (slides)
- Lecture 7: Nonlinear regression (cont) (slides)
- Lecture 8: Classification (slides)
- Lecture 9: Classification (cont), evaluating ML algorithms (slides)
- Lecture 10: Evaluating ML algorithms (slides)
- Lecture 11: Evaluating ML algorithms (cont), electric power systems (slides)
- Lecture 12: DC and AC Circuits (slides)
- Lecture 13: AC Circuits, Power, Generators, and Three Phase Power (Online lecture) (slides)
- Lecture 14: Power flow (slides)
- Lecture 15: Optimal power flow, power markets (slides)
- Lecture 16: Power markets (cont), power electronics (slides)
- Lecture 17: Control introduction (slides)
- Lecture 18: Control examples, dynamical systems (slides)
- Lecture 19: Dynamical systems (cont) (slides)
- Lecture 20: Stochastic Systems, PID Control (slides)
- Lecture 21: Multivariate systems, LQR (slides)
- Lecture 22: LQ Stochastic Control, MDPs (slides)
- Lecture 23: Model Predictive Control (slides)
- Lecture 24: Future Directions in Smart Grid Research (slides)
Other Resources:
- Course Information and Syllabus (updated 8/26/13)
- Review Notes: Linear Algebra
- MATLAB Tutorial
Optional Textbooks:
Taken together, these textbooks cover most of the material we cover in this class. This list is strictly optional reading for those who might want to pursue one of the topics more deeply; the slides themselves cover everything that will be needed for the homeworks, and these books together cover substantially more material than what we cover in class.
- Machine Learning: C. Bishop. Pattern Recognition and Machine Learning.
- Optimization: S. Boyd, L. Vandenberghe. Convex Optimization. (available online)
- Electrical power systems: A. von Meier. Electric Power Systems: A Conceptual Introduction.
- Model predictive control: E. F. Camacho and C. Bordons. Model Predictive Control.