Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings

Chen, Zhelun; Wen, Jin; Li, Yicheng; Lo, L. James; Grajewski, Gabriel; Payne, W. Vance; Bushby, Steven T.; Pertzborn, Amanda; O’Neill, Zheng; Yang, Zhiyao; Calfa, Caleb

doi:10.1080/23744731.2024.2394357

Title: Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings

Journal Article · Mon Sep 02 00:00:00 UTC 2024 · Science and Technology for the Built Environment

DOI: https://doi.org/10.1080/23744731.2024.2394357 · OSTI ID:2530704

^[1]; Wen, Jin ^[1]; Li, Yicheng ^[1]; Lo, L. James ^[1]; Grajewski, Gabriel ^[1]; Payne, W. Vance ^[2]; Bushby, Steven T. ^[2]; Pertzborn, Amanda ^[2];

^[3]; Yang, Zhiyao ^[3];

^[3]

Drexel University, Philadelphia, PA (United States)
National Institute of Standards and Technology, Gaithersburg, MD (United States)
Texas A&M University, College Station, TX (United States)

With buildings contributing significantly to electricity usage, enabling demand flexibility becomes a challenge, especially when accounting for occupant comfort. This study introduces an innovative co-simulation framework integrating multiple models: heating, ventilation, and air conditioning (HVAC) system, building zone load, indoor airflow, supervisory control, and occupant comfort and behavior. Uniquely, this framework allows for a comprehensive and dynamic analysis of building systems and occupant interactions in demand response events. Using this framework, we conducted a case study using a typical small office building model. Specifically, we focused on three areas: (1) the impact of indoor airflow modeling on energy use, occupant comfort, and behaviors forecasting, (2) the impact of occupant behaviors on demand flexibility, and (3) occupant comfort and behaviors under demand response events. Key performance indicators such as energy use, flexibility factor, durations of occupant discomfort and occupant behaviors were analyzed. Our findings indicated variations in energy usage and occupant comfort within demand flexibility events, marked by uncertainty boundaries, with variability in demand shedding up to 57.9%. Here, we concluded that this framework is suitable for analyzing typical commercial buildings and their HVAC systems in terms of demand flexibility potential under the impact of occupant behaviors.

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Research Organization:: Drexel University, Philadelphia, PA (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: EE0009153

OSTI ID:: 2530704

Journal Information:: Science and Technology for the Built Environment, Journal Name: Science and Technology for the Built Environment Journal Issue: 9 Vol. 30; ISSN 2374-4731

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

References (26)

EnergyPlus: creating a new-generation building energy simulation program Crawley, Drury B.; Lawrie, Linda K.; Winkelmann, Frederick C. Energy and Buildings, Vol. 33, Issue 4 https://doi.org/10.1016/S0378-7788(00)00114-6	journal	April 2001
Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives Li, Han; Johra, Hicham; de Andrade Pereira, Flavia Applied Energy, Vol. 343 https://doi.org/10.1016/j.apenergy.2023.121217	journal	August 2023
Modeling thermal comfort holistically: Bayesian estimation of thermal sensation, acceptability, and preference distributions for office building occupants Langevin, Jared; Wen, Jin; Gurian, Patrick L. Building and Environment, Vol. 69 https://doi.org/10.1016/j.buildenv.2013.07.017	journal	November 2013
A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices Gunay, H. Burak; O'Brien, William; Beausoleil-Morrison, Ian Building and Environment, Vol. 70 https://doi.org/10.1016/j.buildenv.2013.07.020	journal	December 2013
Simulating the human-building interaction: Development and validation of an agent-based model of office occupant behaviors Langevin, Jared; Wen, Jin; Gurian, Patrick L. Building and Environment, Vol. 88 https://doi.org/10.1016/j.buildenv.2014.11.037	journal	June 2015
Demand response potential of electrical space heating in Swedish single-family dwellings Nyholm, Emil; Puranik, Sanket; Mata, Érika Building and Environment, Vol. 96 https://doi.org/10.1016/j.buildenv.2015.11.019	journal	February 2016
Analyzing the effects of comfort relaxation on energy demand flexibility of buildings: A multiobjective optimization approach Morales-Valdés, Pilar; Flores-Tlacuahuac, Antonio; Zavala, Victor M. Energy and Buildings, Vol. 85 https://doi.org/10.1016/j.enbuild.2014.09.040	journal	December 2014
Agent-based stochastic model of thermostat adjustments: A demand response application Vellei, Marika; Martinez, Simon; Le Dréau, Jérôme Energy and Buildings, Vol. 238 https://doi.org/10.1016/j.enbuild.2021.110846	journal	May 2021
Residential Demand Flexibility: Modeling Occupant Behavior using Sociodemographic Predictors Olawale, Opeoluwa Wonuola; Gilbert, Ben; Reyna, Janet Energy and Buildings, Vol. 262 https://doi.org/10.1016/j.enbuild.2022.111973	journal	May 2022
Peak load shifting control using different cold thermal energy storage facilities in commercial buildings: A review Sun, Yongjun; Wang, Shengwei; Xiao, Fu Energy Conversion and Management, Vol. 71 https://doi.org/10.1016/j.enconman.2013.03.026	journal	July 2013
Quantification of electricity flexibility in demand response: Office building case study Chen, Yongbao; Chen, Zhe; Xu, Peng Energy, Vol. 188 https://doi.org/10.1016/j.energy.2019.116054	journal	December 2019
Quantifying uncertainty in the aggregate energy flexibility of high-rise residential building clusters considering stochastic occupancy and occupant behavior Hu, Maomao; Xiao, Fu Energy, Vol. 194 https://doi.org/10.1016/j.energy.2019.116838	journal	March 2020
A data-driven study of thermostat overrides during demand response events Sarran, Lucile; Gunay, H. Burak; O'Brien, William Energy Policy, Vol. 153 https://doi.org/10.1016/j.enpol.2021.112290	journal	June 2021
Investigating willingness to save energy and communication about energy use in the American workplace with the attitude-behavior-context model Xu, Xiaojing; Maki, Alexander; Chen, Chien-fei Energy Research & Social Science, Vol. 32 https://doi.org/10.1016/j.erss.2017.02.011	journal	October 2017
Tracking the human-building interaction: A longitudinal field study of occupant behavior in air-conditioned offices Langevin, Jared; Gurian, Patrick L.; Wen, Jin Journal of Environmental Psychology, Vol. 42 https://doi.org/10.1016/j.jenvp.2015.01.007	journal	June 2015
Uncertainty analysis of occupant behavior and building envelope materials in office building performance simulation Belazi, Walid; Ouldboukhitine, Salah-Eddine; Chateauneuf, Alaa Journal of Building Engineering, Vol. 19 https://doi.org/10.1016/j.jobe.2018.06.005	journal	September 2018
From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency Jia, Mengda; Srinivasan, Ravi S.; Raheem, Adeeba A. Renewable and Sustainable Energy Reviews, Vol. 68 https://doi.org/10.1016/j.rser.2016.10.011	journal	February 2017
State-of-the-art review of occupant behavior modeling and implementation in building performance simulation Ahmed, Omar; Sezer, Nurettin; Ouf, Mohamed Renewable and Sustainable Energy Reviews, Vol. 185 https://doi.org/10.1016/j.rser.2023.113558	journal	October 2023
The impacts of occupant behavior on building energy consumption: A review Chen, Shuo; Zhang, Guomin; Xia, Xiaobo Sustainable Energy Technologies and Assessments, Vol. 45 https://doi.org/10.1016/j.seta.2021.101212	journal	June 2021
Aggregate residential demand flexibility behavior: A novel assessment framework Wonuola Olawale, Opeoluwa; Gilbert, Ben; Reyna, Janet Sustainable Energy Technologies and Assessments, Vol. 56 https://doi.org/10.1016/j.seta.2023.103073	journal	March 2023
Modelling uncertainty in district energy simulations by stochastic residential occupant behaviour Baetens, Ruben; Saelens, Dirk Journal of Building Performance Simulation, Vol. 9, Issue 4 https://doi.org/10.1080/19401493.2015.1070203	journal	July 2015
Performance assessment of a real water source heat pump within a hardware-in-the-loop (HIL) testing environment Calfa, Caleb; Yang, Zhiyao; Li, Yicheng Science and Technology for the Built Environment, Vol. 29, Issue 10 https://doi.org/10.1080/23744731.2023.2261810	journal	October 2023
Table for Estimating the Goodness of Fit of Empirical Distributions Smirnov, N. The Annals of Mathematical Statistics, Vol. 19, Issue 2 https://doi.org/10.1214/aoms/1177730256	journal	June 1948
On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other Mann, H. B.; Whitney, D. R. The Annals of Mathematical Statistics, Vol. 18, Issue 1 https://doi.org/10.1214/aoms/1177730491	journal	March 1947
Implementing Occupant Behaviour in the Simulation of Building Energy Performance and Energy Flexibility: Development of Co-Simulation Framework and Case Study Li, Rongling; Wei, Feng; Zhao, Yang Building Simulation Conference Proceedings https://doi.org/10.26868/25222708.2017.211	conference	August 2017
A Simulation Framework for Analyzing the Impact of Stochastic Occupant Behaviors on Demand Flexibility in Typical Commercial Buildings Chen, Zhelun; Li, Yicheng; Wen, Jin 2023 ASHRAE Annual Conference https://doi.org/10.63044/s23che04	conference	April 2024

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
commercial buildings HVAC
demand flexibility
grid-interactive efficient buildings
occupant behavior
thermal comfort

Title: Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings

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