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).