We assessed the difference between mean radiant temperature (! ) and air temperature (! ) in conditioned office buildings to provide guidance on whether practitioners should separately measure ! or operative temperature to control heating and cooling systems. We used measurements from 48 office buildings in the ASHRAE Global Thermal Comfort Database, five field studies in radiant and all-air buildings, and five test conditions from a laboratory experiment that compared radiant and all-air cooling. The ASHRAE Global Thermal Comfort Database is the largest of these three datasets and most representative of typical thermal conditions in an office; in this dataset the median absolute difference between ! and ! was 0.4 (with 5 th , 25 th , 75 th , and 95 th percentiles = 0.2, 0.2, 0.6, and 1.6 °C). More specifically, the median difference shows that was 0.4 warmer than (with 5 th , 25 th , 75 th , and 95 th percentiles = -0.4 °C, 0.2 °C, 0.6 °C, and 1.6 °C). The laboratory experiments revealed that in a radiant cooled space ! was significantly (p<0.05) cooler than ! (average difference -0.1 ! ), while in the all-air cooled space ! was significantly (p<0.05) warmer than ! (average difference +0.3 ! ). These observations indicate that ! and ! are typically closer in radiant cooled spaces than in all-air cooled spaces. Although the differences are significant, the effect sizes are negligible to small based on Cohen's d and Spearman's rho. Therefore, we conclude that measurement of ! is sufficient to estimate ! under typical office conditions, and that separate measurement of ! or operative temperature is not likely to have practical benefits to thermal comfort in most cases -this is especially true for buildings with radiant systems. Furthermore, spatial and temporal variations in ! can be greater than or equal to the difference between ! and ! at any one location in a thermal zone, thus we expect that such variations typically have a greater impact on occupant thermal comfort than the differences between ! and ! .
Radiant cooling systems extract heat from buildings differently than all-air cooling systems. These differences impact the time and rate at which heat is removed from a space, as well as the total amount of thermal energy that a mechanical system must process each day. In this article we present measurements from a series of multi-day side-by-side comparisons of radiant cooling and all-air cooling in a pair of experimental testbed buildings, with equal heat gains, and maintained at equivalent comfort conditions (operative temperature). The results show that radiant cooling must remove more heat than all-air cooling-2% more in an experiment with constant internal heat gains, and 7% more with periodic scheduled internal heat gains. Moreover, the peak sensible space heat extraction rate for radiant cooling (heat transfer at the cooled surface, not the cooling plant) must be larger than the peak sensible space heat extraction rate for all-air systems, and it must occur earlier. The daily peak sensible space heat extraction rate for the radiant system was 1-10% larger than for the all air system, and it occurred 1-2 hours earlier. These findings have consequences for the design of radiant systems. In particular, this study confirms that cooling load estimates for all-air systems will not represent the space heat extraction rates required for radiant systems.
Occupant presence and behavior can and should influence energy use in buildings. If occupancy is measured, predicted, or otherwise inferred, building controls can automatically adjust system operating parameters to use less energy without sacrificing user services. However, previous field evaluations and simulation studies appear to have overestimated the energy savings associated with this type of smart control. In this article we present results from a carefully controlled field evaluation of occupancyresponsive learning thermostats installed in every bedroom of three high-rise university residence halls. While a standard practice energy model developed prior to the retrofit estimated 10-25% savings for cooling and 20-50% savings for heating, measurements reveal that the control scheme only reduced energy consumption by 0-9% for cooling, and by 5-8% for heating for normal operation during academic periods. However, for non-academic periods when the residence halls were sparsely populated, the scheme reduced cooling energy consumption by 20-30%. We analyzed these observations in relation to occupancy patterns, room temperature records, ambient conditions, and equipment run time. The findings provide novel insight about how to improve field evaluations and refine model assumptions to better predict the impact of occupancy-responsive thermostat controls. Notably, while analysts often use fractional building occupancy trends to simulate building energy performance, this study highlights the importance of accounting accurately for both the temporal and spatial variation of vacancy events throughout a building.
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