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A Simulation Framework for Analyzing the Impact of Stochastic Occupant Behaviors on Demand Flexibility in Typical Commercial Buildings



Zhelun Chen, Yicheng Li, Jin Wen, Liang Chung Lo, Gabriel Grajewski, Zheng O'Neill, Amanda Pertzborn, Vance (Wm.) Payne, Steven T. Bushby


As one of the primary users of the electric grid, buildings and building equipment, including heating, ventilation, and air conditioning (HVAC) systems, can be leveraged to provide the flexible demand needed to balance the grid. Typical strategies to achieve demand flexibility are to reduce electricity use during peak or critical periods by shutting down equipment or relaxing system setpoints, which will inevitably impact the occupants' comfort. When occupants feel uncomfortable, they may take actions to regain their comfort, and some of those actions (such as turning on a personal fan) may have a negative impact on meeting the demand response goal. Therefore, it is important to incorporate occupant behaviors into the assessment of the building demand flexibility potential. In this study, a simulation framework that includes simulation of zone thermal loads, an HVAC system, and occupant behaviors, was developed to investigate the impact of occupant behaviors on demand flexibility. A case study was conducted using a small office model from the U.S. Department of Energy (DOE) Commercial Prototype Building Models to simulate the building envelope and zone loads. An agent-based occupant thermal behavior model was adapted to forecast occupants' thermal comfort and their resulting thermal behaviors. An artificial neural network (ANN) based airflow model was trained from a computational fluid dynamics (CFD) model of the zone to better predict the ambient environment of each occupant. An air-source heat pump simulation model that was calibrated from a real two-stage air-source heat pump system was used as the HVAC system. A typical load shedding event during peak hours was studied. Repeated simulations were conducted to capture the stochastic effects of occupant behaviors. By evaluating key performance indicators, including the energy use, occupant discomfort duration, and occupant behavior duration, during the peak period, the demand flexibility uncertainty under the influence of occupant behaviors and occupant comfort and behavior uncertainty under the influence of the demand response event can be captured. The results suggest that this framework can be used to analyze typical commercial buildings and their HVAC systems in terms of demand flexibility potential under the impact of occupant behaviors.
Proceedings Title
2023 ASHRAE Annual Conference
Conference Dates
June 24-28, 2023
Conference Location
Tampa, FL, US


load flexibility, HVAC, occupant behavior, heat pump


Chen, Z. , Li, Y. , Wen, J. , Lo, L. , Grajewski, G. , O'Neill, Z. , Pertzborn, A. , Payne, V. and Bushby, S. (2023), A Simulation Framework for Analyzing the Impact of Stochastic Occupant Behaviors on Demand Flexibility in Typical Commercial Buildings, 2023 ASHRAE Annual Conference, Tampa, FL, US, [online], (Accessed June 18, 2024)


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Created June 27, 2023, Updated September 19, 2023