An Interactive Task-Ambient Cooling Control Featuring Personal Thermal Comfort and Non-Intrusive Sensing Techniques

The Heating, Ventilation and Air-Conditioning (HVAC) system plays a key role in shaping building performances. Effective and efficient HVAC operations not only achieve energy savings but also create a more comfortable indoor environment for occupants. Moreover, compared to the
private office environment, the open-plan office environment has become a trend in most office buildings since it not only creates opportunities for employees to communicate with one another and improves productivity but also reduces construction cost. However, the open-plan office
building layout is also faced with problems such as interruptions from other people and unsatisfactory shared indoor temperature and humidity levels. Therefore, it is of great importance to develop a new paradigm for the HVAC system framework so that everyone can work under
their preferred thermal environment while also achieving improved energy performance. But how can we achieve personal thermal comfort and energy efficiency without being intrusive? This dissertation proposes a new integrative task-ambient cooling control featuring personal comfort models with non-intrusive sensing techniques for open-plan office spaces. The research mainly consists of four parts:
• Development of a personalized cooling control to create a comfortable local thermal environment automatically with non-intrusive sensing techniques and machine learning
algorithms. The sensing system consists of an indoor air temperature sensor, relative humidity sensor DHT22, and an infrared temperature sensor AMG8833.
• Quantification of the energy savings of the proposed task-ambient cooling system by cooling set-point optimization of the ambient conditioning system and the automatic operations of the task conditioning systems with personal thermal comfort models.
• Development of a data-driven approach with CFD simulator to analyze the benefits of energy savings in a typical office space while maintaining acceptable thermal comfort with the
proposed task-ambient cooling system.
• Development of an energy co-simulation with the proposed task-ambient cooling system to analyze the benefits of energy savings in a typical shared office space while maintaining acceptable thermal comfort with comfort database I & II.
As a result, in terms of energy savings, five 3-hour sessions in the field study have shown that the proposed system can achieve 9.6% in HVAC energy savings on average compared withbaseline system. Moreover, the energy co-simulation study has shown the energy performances with the proposed task-ambient cooling system could be optimized to save HVAC electric demand power by 5.3% on average compared with baseline system. Additionally, in terms of thermal comfort, the performances in the field study have shown the recall scores of the thermal sensation model and the thermal satisfaction model with data from all female subjects are 84.7% and 76.5%, respectively. Meanwhile, the recall scores of the thermal sensation and the thermal satisfaction model with data from all male subjects are 87% and 82.5%, respectively. Furthermore, an automated feedback collection mechanism was implemented to
update personal comfort models by collecting override actions by occupants (collecting the information of thermal environment conditions when occupants manually change on/off overriding the programmed automation system). As a result, participants were more satisfied with updated personal comfort models. Overall, the proposed task-ambient cooling system featuring personal thermal comfort and non-intrusive sensing techniques not only optimizes energy performance, but also provides a more
comfortable thermal environment in open plan office spaces.