Abstract: Buildings consumed 45% of U.S. primary energy consumption (73% of all electricity) in 2017, contributed 39% of national CO2 emissions, and constitute a $395 billion/yr national energy bill. Building energy modeling (BEM) can be used to find the most cost-effective energy conservation measures for a building, but more scalable approaches are needed for industry to make actionable business decisions. Development of urban-scale building energy models is becoming increasingly tractable for many applications including city-wide energy supply/demand strategies, urban development planning, electrical grid stability, and urban resilience.
I will discuss Oak Ridge National Laboratory’s Automatic Building detection and Energy Modeling (AutoBEM) technologies for creating models of buildings at university campuses and city-sized areas. A case study for creating a digital twin of an electrical utility and evaluating value propositions for BEM-leveraged use cases will be discussed that was enabled via partnership from the Electric Power Board (EPB) of Chattanooga and involves comparison to 15-minute data from over 150,000 buildings.
Bio: Joshua New is a computer scientist at Oak Ridge National Laboratory. He received his Ph.D. in computer science at the University of Tennessee and his M.S. in computer systems and software design and his B.S. in computer science and mathematics from Jacksonville State University.