EE392n: Intelligent Energy Systems: Energy and Big Data

Stanford University, Spring Quarter 2013-2014

Daniel C. O’Neill and Dimitry Gorinevsky

Basic course information

Units: 1

Lectures: Hewlett Room 102, Tuesdays, 4:15-5:05PM

Coordinators: Daniel C. O’Neill, Packard 223, (650) 575-1367, and Dimitry Gorinevsky, Packard 233, (650) 724-6783,

Office hours: Tuesdays, 3 pm to 4 pm, Packard 223, and Thursdays, 3 pm to 4 pm, Packard 233,

Textbook and optional references: There is no textbook. Lecture notes will be available in Adobe acrobat (pdf) from the class web page,

Course requirements:

Homework: This is a seminar course and no homework will be assigned.

Grading: CR/NC

Prerequisites: (helpful but not mandatory) Stat 116; EE263 or Eng 207a; basic communications

Catalog description: The course will focus on Data Science techniques in modern energy systems and on the infrastructure required to support such techniques. The main focus will be on Big Data applications. The goal of the course is to prepare the students for careers in energy related areas by teaching systems engineering perspective. The course will discuss analytics for monitoring of the power generation systems, power transmission and distribution systems, asset management, and energy use in buildings. The examples and case studies illustrating the analytics functions and information systems in energy will be presented by prominent guest lecturers from industry.