U.S. Department of EnergyOffice of Scientific and Technical Information
A Mobility-Driven Approach to Modeling Building Energy
Abstract
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.
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1649515
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Conference
- 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
Citation Formats
Berres, Andy, Im, Piljae, Kurte, Kuldeep, Dumas, Melissa, Thakur, Gautam Malviya, and Sanyal, Jibo. A Mobility-Driven Approach to Modeling Building Energy. United States: N. p., 2019.
Web. doi:10.1109/BigData47090.2019.9006308.
Berres, Andy, Im, Piljae, Kurte, Kuldeep, Dumas, Melissa, Thakur, Gautam Malviya, & Sanyal, Jibo. A Mobility-Driven Approach to Modeling Building Energy. United States. https://doi.org/10.1109/BigData47090.2019.9006308
Berres, Andy, Im, Piljae, Kurte, Kuldeep, Dumas, Melissa, Thakur, Gautam Malviya, and Sanyal, Jibo. 2019.
"A Mobility-Driven Approach to Modeling Building Energy". United States. https://doi.org/10.1109/BigData47090.2019.9006308. https://www.osti.gov/servlets/purl/1649515.
@article{osti_1649515,
title = {A Mobility-Driven Approach to Modeling Building Energy},
author = {Berres, Andy and Im, Piljae and Kurte, Kuldeep and Dumas, Melissa and Thakur, Gautam Malviya and Sanyal, Jibo},
abstractNote = {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.},
doi = {10.1109/BigData47090.2019.9006308},
url = {https://www.osti.gov/biblio/1649515},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {12}
}