Faculty: Pedro Manuel Santos de Carvalho

Student: Antonio Vitor da Cruz Villas Boas

The Smart Grid has been evolving by (i) making available a plethora of data from monitoring technologies and (ii) making use of such data to advance grid management and control in order to embed high levels of renewable power generation.

In this context, the challenges faced by engineers and data scientists are evolving very fast. Such challenges demand for both specific skills in data analytics and a deep understanding of the power system. This course aims at providing neither of these – each of these topics is covered in great depth by other courses. This course aims at providing the basic knowledge about grids to translate power systems domain expertise into learning bias, and with this knowledge empower students to develop useful analytics for predicting and learning from grid’s high dimensional data.

The course is organized to progressively introduce the structural properties of electrical distribution grids and the required domain expertise necessary to use such properties in learning from grid data. We address the main learning approaches and corresponding models, sometimes oversimplifying the problems. The focus is directed to understanding how to build-in structural knowledge about grids, not to dealing with the many contextual details of practical applications.