Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763712
Title: Adaptive thermal comfort and its application in mixed mode buildings : the case of a hot-summer and cold-winter climate in China
Author: Chen, Rongweixin
ISNI:       0000 0004 7652 5727
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2018
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Abstract:
It is widely recognised that one's ability of adaptation is remarkable and thermal comfort is significantly related to such adaptations. This study proposes an alternative method of predicting adaptive thermal comfort based on the availability of adaptations, in particular behavioural adaptations, which needs quantifications of individual adaptation processes and of interactions between them. The fundamental argument of this method is that exercising an adaptive behaviour leads to an increase in comfort temperature, which is termed adaptive increment in this study. Apart from adaptive increments, this method also determines a baseline thermal comfort temperature (the thermal comfort temperature without adaptations) and a correction factor that considers the factors affecting adaptive behaviours, based on which, the highest operative temperature at which people may still feel thermally comfortable. This may be applied in mixed mode (MM) buildings to achieve a higher air-conditioning (AC) setpoint which may lead to a significant reduction in cooling energy. This method is believed to be flexible in dealing with different environments with various levels of adaptations and likely to be advantageous over the steady-state and adaptive models in predicting thermal comfort temperature of an environment with abundant adaptive opportunities. This study also evaluates ways of promoting the use of adaptive opportunities. It explores how adaptive thermal comfort theories may be used for behaviour modelling and in turn be applied to enhance the energy performances and comfort levels of real buildings. To improve the feasibility of this method key effective adaptive behaviours are studied in detail through lab experiments and field studies. The lab experiment has found the adaptive increment of taking cold water to be 1.5°C which is more significant than the previous literature suggests. When all the studied adaptive behaviours are exercised, the overall adaptive increment is as high as 4.7°C. However, the research has identified some issues associated with the adaptive opportunities studied. These include the existence of constraints on the use of adaptive behaviours, the low availability of some effective adaptive opportunities, the low operation frequency of desk fans and the misuse of windows and AC systems. Despite this, the availability of more adaptive opportunities has been verified to be capable of increasing the highest operative temperature at which people may still feel thermally comfortable: the lab experiment shows that over 80% of the participants can still find it thermally comfortable at an operative temperature of 30°C on the condition that adequate adaptive opportunities are provided; the field study shows that the thermal comfort temperature of occupants increases by at least 1°C when desk fans and cool mats are available. Based on these analyses, it proposes an MM system which encourages occupants to exercise adaptive opportunities and improves both comfort levels and energy efficiency. Building performance simulation results show that the proposed MM system is effective in reducing the reliance on AC systems and promotes effective uses of windows and AC systems. By applying the MM system and the associated passive energy-saving strategies, an office can cut cooling energy by about 90% and the peak cooling load by over 80% during transitional seasons.
Supervisor: Steemers, Koen Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.763712  DOI:
Keywords: Adaptive thermal comfort ; Alternative thermal comfort model ; Mixed mode buildings ; stochastic behaviour model ; adaptive increment
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