Grid-Interactive Efficient Buildings (GEBs) are a great tool for carbon emissions reduction, but they are incredibly complex. A new course offered through the University of Texas at Austin and the Intelligent Environments Lab seeks to demystify GEBs.
Zoltán Nagy, a professor at the University of Texas at Austin and director of the school's Intelligent Environments Laboratory (IEL), recently created a public course on Grid-Interactive Efficient Buildings (GEBs). A GEB is an energy-efficient building that uses smart end-use equipment and/or other onsite resources like solar PV to provide demand flexibility while also optimizing for energy cost, grid services, and occupant needs and preferences. The promise of GEBs is tantalizing for those concerned with reducing the 40% of global carbon emissions that come from buildings. But a complex web of existing building systems, communication protocols, operating constraints, and incentives can be overwhelming in their complexity.
The UT course attempts to simplify this complexity and introduce participants to new concepts in GEBs. The graduate-level UT course focuses on the intersection of building energy systems, occupant comfort, and grid interaction. Participants learn about harnessing machine learning techniques to optimize building operations and energy efficiency while considering occupant comfort and preferences. The course, available for free on GitHub, includes lecture notes, programming activities, tutorials, assignments, and recordings from guest lecturers. Guest lectures focused on:
See Tanya's guest lecture, "Separating Fact from Fiction" in the sidebar!
