Data, Environment and Society (ENE,RES 131)
This course teaches students to build, estimate, and interpret models that describe phenomena in the broad area of energy and environmental decision-making. Students leave the course as both critical consumers and responsible producers of data-driven analysis. The effort is divided between (i) learning a suite of data-driven modeling and prediction tools (including linear model selection methods, classification and regression trees, and support vector machines); (ii) building the programming and computing expertise to use those tools; and (iii) developing the ability to formulate and answer resource allocation questions within energy and environment contexts. We work in Python in this course, and students must have taken Data 8 before enrolling. The course is designed to complement and reinforce Berkeley’s data science curriculum.
Text: James et al, An Introduction to Statistical Learning.
Electric Power Systems (ENE,RES 254)
This course provides an understanding of concepts in the design and operation of electric power systems, including generation, transmission, and consumption. We cover basic electromechanical physics, reactive power, circuit and load analysis, reliability, planning, dispatch, organizational design, regulations, environment, end-use efficiency, and new technologies.
21st Century Power System Dynamics (EECS 290O)
This is a graduate seminar covering the intersection of classical power system dynamics with the dynamics of generation that interfaces with the grid via power electronic converters. This is an emerging research area with a relatively small body of work to learn from. We will learn about classical approaches to modeling power system dynamics, approaches to modeling converters in power systems, and the state-of-the-art with respect to controlling converter power and voltage output. We’ll spend some class time in traditional lecture format (with graduate students delivering some of the content), and the remainder of class time doing paper presentations and discussion.
Note: In the Fall of 2021, this was run as the UNIFI Seminar Series — more information here.