Leveraging divergences: building control, personal comfort and indoor climate

Date

2023-6-19

Author

Topak, Fatih

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Over the last two decades, major advances in technology have allowed researchers to develop strategies for automating the operational tasks in buildings to improve the overall system efficiency. However, the stochastic nature of human needs and standardized, one-size-fits-all configurations in current control approaches lead to disharmony in human-automation coexistence in buildings. Although well-established interaction between control systems and occupants is acknowledged as one of the core elements of intelligent buildings, defined borderlines of the prevailing automation modalities fail to satisfy this primary feature. To this end, this research conceptualizes a collaborative building control framework, which establishes a communication ground between people and buildings. To assess comfort and energy related implications of the proposed framework, a simulation based and data driven research was conducted in the thermal domain, considering the need for investigating the personalized dimensions of building control, human comfort, and indoor climate. A multi-occupancy office space shared by six occupants was adopted as a case study. Probabilistic personal comfort profiles were used to quantify the likelihood of each occupant being comfortable in diverse conditions. Thermal distribution characteristics of the space were investigated using computational fluid dynamics (CFD) simulations under varying supply airflow rates, supply airflow directions, and occupancy settings. Through performing an optimization analysis, achievable comfort improvements and energy savings were presented. The results confirmed that considering the divergences in personal comfort and indoor climate with a dynamic control strategy, where occupants are kept in the loop, has great potential for providing comfortable indoor environmental conditions and improving energy efficiency.

Subject Keywords

Building control, Thermal comfort, Energy efficiency, personal comfort models, Computational fluid dynamics, Occupant-centric building operation

URI

https://hdl.handle.net/11511/104451

Collections

Graduate School of Natural and Applied Sciences, Thesis