Buildings account for a large fraction of our nation's energy consumption and CO2 emissions. Enhancing energy efficiency of both commercial and residential buildings is a crucial step in improving the nation's energy security, lowering costs, and improving environment through emission reduction. Since a major reason behind the inefficiency is the way buildings are operated and controlled, advanced control systems are expected to play a pivotal role in reducing - if not removing - these inefficiencies. Several hurdles will have to be overcome in order to achieve performance beyond what current building control systems can provide. These come from not only the complex nature of the underlying physical phenomenon that determines energy consumption in a building, but also the stringent health and comfort requirements, as well as the uncertainties introduced by the behaviors and choices of the building occupants the owners/designers/operators. On the other hand, predictive models are crucial to make decisions that will minimize energy consumption while ensuring health and comfort of the building occupants. Due to the inherent uncertainties, the control algorithms have to be robust to a large degree of error in the predictions and measurements. In this talk we will describe our ongoing work on developing such models and control algorithms, lessons learned, and future challenges.
Prabir Barooah was born in Jorhat, Assam (India). He received the Ph.D. degree in Electrical and Computer Engineering in 2007 from the University of California, Santa Barbara. From 1999 to 2002 he was a research engineer at United Technologies Research Center, East Hartford, CT. He received the M. S. degree in Mechanical Engineering from the University of Delaware in 1999 and the B.Tech degree in Mechanical Engineering from the Indian Institute of Technology, Kanpur, in 1996. Dr. Barooah is the winner of the NSF CAREER award (2010), General Chairs' Recognition Award for Interactive papers at the 48th IEEE Conference on Decision and Control (2009), best paper award at the 2nd Int. Conf. on Intelligent Sensing and Information Processing (2005), and NASA group achievement award (2003).
