Units: 3
Slots: 60-120, Monday and Wednesday, 4:15-5:30PM
Grading: Letter or Credit/No Credit
Prerequisites: Instructor approval required. You need to contact the instructors before you register on axess.
Coordinators:
Daniel C. O’Neill
Packard 223, (650) 575-1367,
dconeill@stanford.edu
Dimitry Gorinevsky Packard 233, (650) 724-6783, gorin@stanford.edu
Administrative Assistant: Denise Murphy, Packard 267, (650) 723-4731, Fax (650) 723-8473, denise@ee.stanford.edu.
Office hours: TBA
Course requirements:
Students will work individually or in teams of up to three students and prepare a written and oral project report, due at the end of the quarter. The oral presentations will be limited to 20 minutes. These presentations will provide the students with an opportunity to crystallize their thoughts, which will be useful when speaking with faculty working in this area or with possible future employers. The written report will be limited to ten pages and divided into four sections:Catalog description:
The emergence of Intelligent Energy Systems is driven by several converging macro factors: anticipated higher energy costs and uncertain availability, the need to replace the aging electrical power infrastructure, and the forecasted availability of alternative sources of clean energy such as wind and solar. Energy systems must have the intelligence to cope with rapid changes in energy supply, demand, distribution, and storage. This intelligence is implemented in information systems as analytical functions that process real time and historical data to enable monitoring, management and optimization of the smart grid. The proposed projects course, Intelligent Energy Projects, is a result of discussions with students seeking a course to explore their energy related ideas and with industrial companies seeking to interact with Stanford. The course will provide students with a venue to investigate their ideas in intelligent energy systems and to present preliminary results to industrial researchers in the area. We anticipate that at the end of the course the students will have gained an appreciation of the challenges associated with their ideas. To manage the scope of potential projects and to give students meaningful feedback, the consent of the instructor will be required for the class enrollment. We anticipate that students taking this course may also enroll in a sister seminar class EE392N Intelligent Energy Systems, where case studies illustrating information systems in energy will be presented by prominent guest lecturers from industry. The proposed projects course will focus on analytical functions in intelligent energy systems. The analytical methods include optimization, control, monitoring, and others. Projects will focus on analytics for energy management in transmission and distribution systems, monitoring of the energy systems, and asset management.
We anticipate projects in the following areas of intelligent energy systems: