Personalizing thermal environment using digital technologies: towards greater occupant wellbeing and decarbonization of buildings

点击翻译按钮获取中文摘要

Buildings generate nearly 40% of global carbon emissions, which is largely driven by energy demand for space heating and cooling to provide occupant comfort. Thermal environment has a great influence on occupant's comfort, health and productivity. Therefore, to meet Canada's 2050 net zero emissions target, it is critical to reduce building energy consumption while ensuring thermally satisfactory environment. The proposed research focuses on developing research tools to personalize heating and cooling experiences with significantly less energy use. In particular, the integration of (1) Internet-connected personal comfort system (PCS) and (2) personal comfort models (PCM) in building design and operation will be investigated. The scope of this proposal targets office buildings. Three short-term objectives are to: (1) characterize multimodal (perceptual, behavioural, physiological, and cognitive) thermal responses that affect occupant comfort, health, and productivity; (2) develop interpretable machine learning (ML) methods to improve transparency and fidelity of PCM; and (3) develop a digital-twin powered simulation tool to test and evaluate integrated HVAC and PCS controls for deep energy savings. First, the proposed research will conduct a series of laboratory experiments with human subjects to create a rich dataset of multimodal thermal responses via various IoT sensors. The dataset will be used to develop an open-source digital human model for the integration into existing design and simulation software to inform key decisions related to occupant comfort, health, and productivity. Next, domain-specific methods for interpretable ML will be developed to improve fundamental understanding about thermal comfort and industry adoption of data-driven environmental control. Common metrics will be proposed to standardize evaluation and benchmarking of ML models in thermal comfort. Lastly, digital twins of sensors, models, and systems will be created to enable realistic testing and evaluation of integrated HVAC and PCS control strategies. A set of optimal control strategies will be identified to promote low-energy, low-carbon building operation while improving occupant comfort in buildings. The above research will be led by the applicant and executed by 8 highly qualified personnel (HQP), including 3 equivalent PhD, 3 master's, and 2 undergraduate students. Trainees will develop (1) fundamental understanding about thermal comfort, (2) hands-on experience with low-energy building technologies, and (3) cutting-edge digital skills for smart building analytics and control applications. The research results will have the potential to greatly advance occupant-centric building design and operation and reduce environmental impacts of buildings while improving the quality of life and prosperity of diverse communities in Canada.