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

• Published in: HVAC&R research Vol. 30; no. 9; pp. 1094 - 1113
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 20-10-2024; Taylor & Francis Ltd
• Subjects: Air conditioning; Air flow; Comfort; Commercial buildings; Demand analysis; Electric power demand; Energy consumption; Energy management; Flexibility; HVAC; HVAC equipment; Impact analysis; Office buildings; Supervisory control; Systems analysis
• ISSN: 2374-4731; 2374-474X
• DOI: 10.1080/23744731.2024.2394357

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%. 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.