Webinar: June 21, 2024 from 10:00 to 11 a.m. Pacific time

Register in advance for this webinar: https://lbnl.zoom.us/meeting/register/tJYrc-6oqDIrGNP3EYKsuuZFFTAw3VwWZ5dC 

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Abstract: ORNL has simulated every U.S. building. As part of a 5-year vision to do so by 2020, ORNL developed the Automatic Building Energy Modeling (AutoBEM) software suite to collect building-specific data, create OpenStudio/EnergyPlus building energy models, simulate on world-class supercomputers, and analyze results. Initially tested in partnership with a utility involving comparison to 15-minute measured electricity use from each of 178,337 buildings, data sources and algorithms were evolved. Several traditional energy efficiency measures, grid-interactive efficient building (GEB) measures, photovoltaics, managed electric vehicle (EV) charging, microgrid, and climate change assessments were made to inform load shape and business decisions for the electrical distributor. Each building was simulated to quantify the energy (kWh), demand (kW), emissions (CO2-eq), and cost ($) savings of each technology, as well as retrofit packages. AutoBEM was then deployed at scale to model and simulate every U.S. building with models for 122.9 million buildings made publicly available. Since 2020, there have been over 50 Non-Disclosure Agreements with partners actively using this building data. To inform decarbonization efforts, all IPCC scenarios have been converted to county-specific, hourly weather from 1980-2100. The purpose of this talk is to provide background regarding the development of AutoBEM, the Model America dataset, future Typical Meteorological Year (fTMY) weather data, and discuss ways in which related data or models are useful to stakeholders.

Presenter: Dr. Joshua New is a Distinguished R&D Staff Member at Oak Ridge National Laboratory. He received his Ph.D. in Computer Science at the University of Tennessee in 2009, has over 180 peer-reviewed publications, managed BEM portfolios totaling $25 million, and led more than 225 projects totaling $350 million over the last 15 years. His expertise involves building energy modeling, supercomputing, Artificial Intelligence, and big data mining. These have been used to generate, simulate, and analyze energy and emissions data of every U.S. building, which has been made publicly available for scalably quantifying energy, demand, emissions, and cost reductions from individual buildings to the entire nation.