Past Courses

The directors of the ECS-Lab teach various courses.

Undergraduate Courses

This undergraduate course provides a solid overview of power and energy systems basics including electrical machines, power systems and electricity markets. This background is used to present latest developments on smart grids including communications architecture, distributed energy resources, demand response and new market mechanisms. The course is self contained requiring only an undergraduate class in optimization as requisite. 

This course provides the student with the basic tools for: the analysis of electrical circuits in transient and steady state; analyse and use relevant mathematical models in electrical circuits starting from Ohm’s Law to frequency response analysis.

This course introduces students to the problem of modeling stochastic systems and processes, presenting techniques and concepts that make up the basis for most analytical models in research operations to describe probabilistic systems.

The objective of the course is to provide the students with theoretical and practical tools to design control systems that guarantee that the processes achieves the static and dynamic specifications in terms of output quality, performance, operational costs and safety. The course is based on the basic methods of mathematical modeling for continuous and discrete systems. The main tools taught are: i) modeling based on transfer functions and block diagrams, ii) state-space modeling, iii) temporal analysis, iv) frequency analysis, v) root locus techniques, vi) design of controllers using time and frequency methods, vii) introduction to linear optimal control LQR y optimal observers (Kalman filters). 

Graduate Courses

This course presents students to modern optimization techniques and their applications in electrical engineering. To accomplish this, the course reviews convex optimization, mixed-integer optimization, optimization under uncertainty and the computational tools needed to solve problems in the fields of Power Systems, Control Systems, Signal Processing, Telecommunications and Electronics. 

This course presents students to various advanced topics in power systems, including aspects related to control, optimization, and electricity markets.

This course introduces several optimization models associated with the economic operation of power systems. The topics covered include: Motivation, Non-Linear Optimization, Economic Dispatch, Unit Commitment, Hydrothermal Coordination, Optimal Power Flow and some of the underlying theory of Electricity Markets. In addition, advanced topics such as flexibility on the demand side, uncertainty considerations and basics elements of dynamic electricity markets are presented. Grading is based on homeworks, 2 tests and final project which represent the main component of the final grade. 

This course presents some of the main control and optimization techniques applied to contemporary problems in power and energy systems. The topics covered in the course include: Motivation, Linear and Nonlinear Optimization Applied to Power Systems, Decomposition Techniques for Large-scale Optimization Problems, Optimization Under Uncertainty, Advanced Formulations and Applications.