A Mobility-Driven Approach to Modeling Building Energy

Conference · Sun Dec 01 00:00:00 EST 2019

DOI:https://doi.org/10.1109/BigData47090.2019.9006308· OSTI ID:1649515

Berres, Andy  ^[1]; Im, Piljae  ^[1]; Kurte, Kuldeep ^[1]; Dumas, Melissa  ^[1]; Thakur, Gautam Malviya  ^[1]; Sanyal, Jibo  ^[1]

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1. ORNL

Buildings are one of the primary energy consumers in any city's energy use [12]. Presence and absence of humans is a major contributing factor to the energy use in a building. In this paper, we present an approach to generating a realistic model of human building occupancy throughout a typical work week. We use the Toolbox for Urban Mobility Systems (TUMS) to generate a synthetic population based on population distribution estimates, we schedule the population's daily commute based on National Household Travel Survey (NHTS) survey data, and we simulate their daily travel patterns using an agent-based transportation simulation (TRANSIMS). We process and fuse the simulation output to produce a list of the first and last seen location of each agent in the simulation. Based on the arrival at the last destination, we map each agent to one of the nearby buildings. Using these agent arrivals, as well as NHTS data, we create an hourly occupancy schedule for each building. We successfully demonstrate this workflow at the example of the Chicago Loop, a major business district in Chicago, Illinois.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1649515
• Resource Relation: Conference: IEEE International Conference on Big Data - Los Angeles, California, United States of America - 12/9/2019 10:00:00 AM-12/12/2019 10:00:00 AM
• Country of Publication: United States
• Language: English