Home › Challenges & Opportunities for Data-Driven Management of Energy Resources in Buildings
Tuesday, February 11, 2014 - 11:45am - 1:00pm
Challenges & Opportunities for Data-Driven Management of Energy Resources in Buildings
Mario Bergés, PhD
Global climate change and resource constraints are forcing all of us to rethink the way we deal with our energy needs. Buildings play a major role in our current and future energy landscape. They currently consume more than two thirds of all the electricity generated in the United States. As a Civil Engineer I am interested in understanding the opportunities that exist for buildings to reshape their electricity demand to meet the upcoming power systems challenges: from understanding how to improve their efficiency, to creating mechanisms to leverage them as active participants in grid services typically performed by generators or large storage devices such as frequency regulation. I am particularly interested in how these goals can be attained by utilizing sensors and actuators deployed in buildings.
My research for the past year or two has focused on increasing occupant awareness of the electricity consumption in buildings by exploiting low-cost data streams for high-value information, particularly through the use of signal processing tools and machine learning techniques. I envision a scenario where facilities can perform inference and automatically learn from different data sources in the building, in order to provide relevant and specific feedback targeted at influencing behavior and reducing consumption. In this talk I will present some of the work I have been doing towards this goal. In particular, I will present a Non-Intrusive Load Monitoring prototype system that we have installed in four buildings around Pittsburgh, along with preliminary results and early findings from our deployments. I will also present my approach to the problem of inter-operability and integration of sensor systems in buildings. Lastly, I will describe some ideas for automating the configuration and training of these systems. The talk will conclude with a discussion on current challenges and future work.
Mario E. Bergés is an assistant professor in the Department of Civil and Environmental Engineering at CMU. He is interested in making use of cost-effective sensor systems to automatically create models and generate insights that can be used to improve the behavior of infrastructure systems, prevent failures, and better plan for the future. He has been working on three different approaches related to this: appliance-level energy feedback through minimally intrusive strategies, sharing sensing and actuation resources at Internet scales, and unsupervised sensor fusion for proactive energy management. His current research interests also include machine learning, signal processing, the Internet of Things and the smart grid. He is the faculty co-director of the IBM Smart Infrastructure Analytics Laboratory at CMU, as well as the director of the Intelligent Infrastructure Research Lab (INFERLab). Among recent awards, he received the Outstanding Early Career Researcher award from FIATECH in 2010. He received his B.Sc. in 2004 from the Instituto Tecnológico de Santo Domingo, in the Dominican Republic; and his M.Sc. and Ph.D. in Civil and Environmental Engineering in 2007 and 2010, respectively, both from Carnegie Mellon University.
Pizza and refreshments will be served at 11:15am in Glennan 420.