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Effect of fee-for-service air-conditioning management in
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balancing thermal comfort and energy usage
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Chen-Peng Chena, Ruey-Lung Hwangb,*, Wen-Mei Shihb
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a
Department of Occupational Safety and Health, China Medical University, No. 91
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Hsueh-Shih Road, Taichung 404, TAIWAN; chencp@mail.cmu.edu.tw (Chen-Peng
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Chen)
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b
Department of Architecture, National United University, 1 Lien-Da, Kung-Ching Li,
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Miaoli 360, TAIWAN; rueylung@nuu.edu.tw (Ruey-Lung Hwang);
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shihwenmei@gmail.com (Wen-mei Shih)
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* Corresponding author; e-mail: rueylung@nuu.edu.tw;
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tel: +886-37-381643; fax: +886-37-354838
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Types of contribution: Original research paper
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Effect of fee-for-service air-conditioning management in
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balancing thermal comfort and energy usage
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Abstract
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Balancing thermal comfort with requirement of energy conservation presents a challenge
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in hot-and-humid areas where the air-conditioning (AC) is frequently used in cooling the
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indoor air. A field survey was conducted in Taiwan to demonstrate the adaptive
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behaviors of occupants in relation to the use of fans and AC in a school building
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employing mixed-mode ventilation where the AC usage was managed under a
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fee-for-service mechanism. The patterns of using windows, fans, and AC as well as the
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perceptions of students toward the thermal environment were examined. The results of
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thermal perception evaluation in relation to the indoor thermal conditions were
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compared to the levels of thermal comfort predicted by the adaptive models described in
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the ASHRAE Standard 55 and EN 15251 and to that of a local model for evaluating the
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thermal adaption in naturally ventilated buildings. A thermal comfort-driven adaptive
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behavior model was established to illustrate the probability of fans/AC usage at specific
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temperature, and compared to the temperature threshold approach to illustrate the
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potential energy saving the fee-for-service mechanism provided. The findings of this
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study may be applied as a reference for regulating the operation of the AC in school
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buildings of subtropical regions.
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Keywords: Mixed mode; Thermal comfort; Fee-for-service; Energy saving
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Introduction
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In recent years, the schools in Taiwan have enthusiastically promoted the mixed mode of
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natural ventilation (NV) and mechanical cooling as a means of ventilation in the
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classroom. The mixed mode is a preferred strategy for the maintenance of indoor
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environmental quality (IEQ) as it provides a balance between the thermal comfort
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required by the students for their study and the energy expenditure consumed by the
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air-conditioning (AC) use. This balance was dynamic―the occupants appeared to be
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more tolerant of high indoor temperature if they had to use the AC at their own expense
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(Hwang et al. 2009a). With this consideration the school administrations in Taiwan have
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begun to adopt a fee-for-service mechanism in the control of the AC use, in which the
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students are allowed to determine when and how to run the AC in the classroom using a
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pre-deposited charge card. The fee-for-service approach was considered user friendly
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and effective, as generally there were less complaints from the occupants and greater
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savings in the electricity bill, and hence had become a predominant mechanism of AC
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management in Taiwanese schools.
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Earlier studies such as Brager et al. (2004) and Raja et al. (2001) suggested that the
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occupant satisfaction with indoor thermal microclimate might be related to the
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availability of environmental controls to the occupants. In addition, the perceptions of
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poor IEQ and incidents of building-related symptoms had been observed in association
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with the availability of environmental controls (Jaakkola et al. 1989; Toftum 2010). With
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the incorporation of adaptive comfort model in the ASHRAE Standard 55 (ASHRAE
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2004) and in the European adaptive standard EN 15251 (CEN 2007) to serve as an
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alternative criterion of thermal comfort, the thermal adaptive approach is now
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recognized as a viable strategy of both improving the occupants’ satisfaction and
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minimizing the energy consumption inside a building. Together with the evaluation of
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energy consumption, The thermal comfort has been increasingly applied as a criterion in
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the assessment of building performance. For example, Calvino et al. (2010) compared
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different strategies of indoor thermal comfort control. In the comparison the
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performance of energy controllers was quantified by two cost functions based on the
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quadratic forms of the overall energy required by the thermal fluid and of the deviation
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from the preferred set point of the predicted mean vote for thermal sensation. Recent
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researches (Dong and Lam 2011; Liu et al. 2012; Murakami et al. 2007; Rijal et al. 2008;
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Zhong et al. 2008) have also shown the impact from the availability of environmental
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controls and their appropriated usage on energy consumption. Murakami et al. (2009)
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evaluated an interactive system that managed the AC energy use by following the
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occupants’ requests and found a saving of 20% more energy compared to the level
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consumed when the AC was maintained at a constant 26°C. Zhong et al. (2008) applied
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an adaptive model in a building in Shanghai, China, and reported a potential saving of
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30% for the energy used in cooling when the environmental controls were made
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available to the occupants. Based on a year-round field study investigating the use of
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environmental controls in 33 Pakistani offices and commercial buildings, Raja et al.
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(2008) developed a behavioral adaptive algorithm for application in predicting the
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occupants’ behaviors toward the energy-saving building design. In Chongqing, China,
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Liu et al. (2012) presented a dynamic process of occupant behaviors of adaptation in
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response to varied thermal conditions that involved technological, personal and
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psychological processes. The results of Dong and Lam (2011) also indicated: an energy
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saving of 18.5% could be achieved with the indoor thermal comfort still being
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adequately maintained when the occupants were allowed to determine the use of
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environmental controls in accordance with their behavioral patterns.
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However, to date the information is still insufficient to illustrate how the energy use
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by the AC in the confined spaces is balanced with the thermal satisfaction requirements
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as affected by the adaptive behaviors of indoor occupants, specifically, the use of
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environmental controls. Here we present the results from a field survey to demonstrate
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the adaptive behaviors of the students in relation to the use of fans and AC in a
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mixed-mode school building managed by the fee-for-service AC control.
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Materials and methods
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Design of field survey
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The study was conducted in a school building employing mixed-mode ventilation in
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middle Taiwan. The school did not have specific regulations in place to control the usage
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of the AC. Using a pre-deposited charge card, the students might activate the AC units
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when they opted to through a control device installed in the classroom, and after each
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use they were alerted of the expense of their AC use by the digital displays on the device.
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The study was performed from April to June of 2011, five days a week when the school
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was in session, and the subjects surveyed were high-school students of an age of 15-16.
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The field study consisted of three components: a questionnaire survey on the student’s
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thermal perception, an on-site measurement of indoor thermal climate, and the
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monitoring on the usage of windows, ceiling fans, and AC.
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To evaluate the change of indoor thermal sensation in relation to the fee-for-service
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energy control, the students were asked to vote on their perceptions toward the thermal
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conditions in the classroom. A copy of the questionnaire used in the thermal comfort
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survey is shown in Table 1. Two surveys were conducted on each school day, with the
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first being performed around 10:00 a.m. and the second about 2:00 p.m. A total of 1,480
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responses were collected to describe the following perceptions:
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
Thermal sensation toward the environment, gauged using the 7-point ASHRAE
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scale of thermal sensation vote (TSV), in which a vote of +3, +2, +1, 0, -1, -2, and
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-3 represented a sensation of hot, warm, slightly warm, neutral, slightly cool, cool,
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and cold sensation, respectively;
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Thermal comfort of the participants, measured on a 6-point thermal comfort scale
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of thermal comfort vote (TCV), in which a vote of +3, +2, +1, -1, -2, and -3
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indicated a very comfortable, comfortable, slightly comfortable, slightly
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uncomfortable, uncomfortable, and very uncomfortable level, respectively;
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Thermal acceptance of the indoor condition, measured using a dichotomous scale
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of thermal acceptability vote (TAV), with the vote of +1 and -1 reflecting
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acceptable and unacceptable perception respectively.
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In addition to the thermal perceptions, the students were also requested to provide
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an hourly record on the opening of windows, use of ceiling fans, or use of the AC so that
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the patterns on the usage of environmental controls in the classroom could be explored.
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To realize the subjective perceptions of the students in relation to the thermal
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conditions in the classroom, the climatic variables including the air temperature (ta),
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relative humidity (RH), globe temperature (tg), and air speed (v) were monitored on-site
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continuously throughout the period of the study. The ta, RH, and tg were recorded using
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a CENTER 314 Temperature/Humidity Datalogger (Center Technology Corp., Taipei,
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Taiwan) and the wind speed using a hot-wired omni-directional DeltaOHM
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thermo-anemometer HD2103.2 (DeltaOHM, Italy) in accordance with the requirements
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in the ISO 7726 on the equipments for thermal environment monitoring (ISO 1998).
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Table 2 summarized the equipments used in climatic monitoring as well as their
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specifications. To interpret the overall effect of the thermal conditions indoors on the
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students’ thermal perceptions and on their use of environmental controls, the ta, RH, and
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v were converted to a single value of operative temperature (top). The top here was the
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average of the ta and the mean radiant temperature (tr) weighted by the convective heat
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transfer coefficient and the liberalized radiant heat transfer coefficient for the occupants.
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In this study, as the students were mostly engaged in near sedentary activity when
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staying in the classroom (with a metabolic rate of 1.0-1.3 met) without direct exposure
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to the sunlight, the top was calculated following the formula presented in the Appendix C
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of the ASHRAE Standard 55 (2004):
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top  w  ta  (1  w)  tr
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(1)
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where the weighting factor (w) was a function of the air speed. The tr was estimated
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using the equation defined in the ISO 7726 (1998):
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tr  [(t g  273) 4  2.5 108  v0.6 (t g  ta )]1/ 4  273
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(2)
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Adaptive thermal comfort criteria for mixed-mode buildings
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For the regulation of indoor thermal comfort in the mixed-mode buildings, the adaptive
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comfort models described in the ASHRAE Standard 55 and the EN 15251 were the two
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criteria most observed worldwide. According to the adaptive model in the ASHRAE
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Standard 55, the optimal operative temperature of thermal comfort indoors (tcomf) could
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be quantitatively related to the average monthly ambient temperature (tom) and expressed
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as:
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tcomf  0.31 tom  17.8
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(3)
10
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In comparison, the EN 15251 defined the tcomf differently in that the monthly mean
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temperature used in deriving the tcomf in the ASHRAE Standard 55 was replaced by a
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running mean temperature (trm) to weight in the influence of the ambient temperatures in
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days prior to the day of observation. The tcomf and trm in the EN 15251 were
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mathematically calculated as:
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t comf  0.33  t rm  18.8
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(4)
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trm 
t1  0.8t 2  0.6t 3  0.5t 4  0.4t 5  0.3t 6  0.2t 7
3.8
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(5)
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where the variables t-1 to t-7 were the daily mean outdoor temperatures one to seven days
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before the observation day, respectively.
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Using the tcomf as a criterion, both the ASHRAE Standard 55 and EN 15251 defined
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the upper and lower limits of temperature for different categories of thermal
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acceptability (Table 3). These categories of acceptability and the boundaries for each in
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top were compared for their applicability serving as criteria in this study for the
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evaluation of the thermal comfort delivered by the fee-for-service energy control.
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Hwang et al. (2009b) performed a long-term field survey among Taiwanese
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students in naturally ventilated (NV) school buildings and reported the adaptive comfort
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zones for 90% and 80% acceptability of 20.1–28.4°C and 17.6–30.0°C (top), respectively.
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As the criteria established in the ASHRAE Standard 55 and the EN 15251 were
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developed using a global or regional database, the findings from Hwang et al. were
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included in this study to serve as locally (Taiwan) based criteria in determining the
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acceptability of indoor thermal conditions. This approach provided an opportunity to
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understand the adjustments that might be desirable when the criteria of thermal
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acceptability established in international standards were applied on a local scale.
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Thermal status and adaptive approach
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Thermal acceptability in relation to distribution of ambient temperature
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The investigation in this study ranged from the 1st of April to the 30th of June and
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covered a period when the climate in Taiwan transitioned from a mild weather in late
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spring into a hot summer. The ambient temperature outside the classroom was monitored
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throughout the study; the measurements were used to derive the tom, trm, and tcomf and to
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interpret the ranges of thermally acceptable top corresponding to the 80% acceptability
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zone as defined in the ASHARE standard 55 and to the Category II acceptability zone in
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the EN 15251, respectively. Fig. 1 shows the distribution of the indoor top in the school
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building employing a mixed-mode ventilation during the course of this study and the
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ranges of thermal acceptability superimposed on the temperature distribution as
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projected by the ASHARE Standard 55 and EN 15251 adaptive models. Overall, the
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average of the maximum, minimum and mean daily temperature during the study period
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was 35.4, 15.4 and 26.1°C, respectively. A comparison of the interpreted values
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indicated that the upper limits of the acceptable range in the EN 15251 were 0.0-2.3ºC
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higher than those in the ASHRAE adaptive standard. In addition, the upper limits of
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acceptable range as defined in the EN 15251 model appeared to be more lenient than
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those of the ASHRAE Standard 55 when applied in Taiwan for evaluating the thermal
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comfort during summer.
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Use of environmental controls in thermal adaption
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Fig. 2 shows, on the thermal comfort chart of ASHRAE Standard 55, the distribution of
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the hourly indoor top by the RH (as expressed in humid ratio) in the classroom in relation
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to the various adaptive approaches the students took when the thermal status varied. The
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top and RH in the situations when the window-opening alone was used for ventilation
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ranged between 19.7-28.3°C and 33-77%, respectively, whereas their counterparts found
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in the situations when the window-opening was used with fans together ranged between
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24.9-32.3°C and 35-86%. The joint use of both fans and the AC as a means of heat
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dissipation occurred when the top and RH were, respectively, 28.9-31.9°C and 42-65%.
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The mean top during the AC use was 30.3°C, 1.3°C higher than the mean value (29.0°C)
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found in the period of fans running (with the windows being opened) and 5.3°C greater
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than the level (25.0°C) observed when the window-opening was used alone.
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In this study, the mechanism of environmental control employed the most by the
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students was a simultaneous use of window-opening and fan-running, which accounted
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for 64% of the total hours of observation. The window-opening alone was the second
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best choice and accounted for 25% of the time. Running both fans and the AC at the
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same time was the least favored (11%). The windows were always open in the classroom
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except when the AC was running—they were open to both control the thermal
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environment as well as to maintain the IEQ. In Taiwan, the students were advised and
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accustomed to keeping the windows of the classroom open throughout the entire year for
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reasons of good IEQ, unless a cold weather was expected or encountered. The low
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proportion of AC operation as a means of thermal adjustment was apparently attributed
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to the concern of the students for the expense with the AC use that they had to pay. The
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AC was never used alone; at all time it was run together with the fans being on, which
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incurred no cost to the students as the school paid for the fan use. The frequent use of the
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fans could also be explained by the potential increase in the upper limit of the acceptable
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indoor temperature due to an enhanced air movement with the fans running. While the
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AC was a choice of thermal adaption, the students used it only when the other
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mechanisms alone or in combination were insufficient to avoid discomfort.
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Table 4 summarized the percentages of the hours when the classroom was occupied
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and the indoor top exceeded the upper bounds of the adaptive thermal comfort criteria
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that the ASHRAE Standard 55, EN 15251, and Hwang et al. described. Although the
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students had the choice of turning the AC on to avoid discomfort, the percentage of the
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hours beyond the 80% acceptability upper limit, from either the ASHRAE 55 or
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Taiwan’s local criteria, was more than one-third of the total hours. Even when the
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thermally lenient Category II of the EN 15251 was used for comparison, the percentage
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was still over 10%. These findings suggested an existence of factors other than the upper
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limit of thermally comfortable top range that influenced the selection of adaptive strategy.
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Among these factors was the expense associated with energy use, which worked against
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the use of AC and indirectly counterbalanced the requirement of the students for thermal
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comfort. However, it remained unclear as to how the requirement for thermal comfort
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and these additional factors, including the cost of AC use, might interact and exert their
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influences in a comprehensive manner.
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Thermal perception under user-controlled energy management
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Distribution of thermal perception
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Table 5 listed the relative distribution of the student’s perception toward the thermal
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status in the classroom as expressed in the TSV, TCV, and TAV. The response of the
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students in this study represented the thermal comfort requirement in the school building
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employing mixed-mode ventilation, where the use of AC could influence the students’
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thermal perception, and this response was compared to those would be observed in a
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naturally ventilated (NV) classroom. The models being compared to included the local
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comfort criteria suggested by Hwang et al. as well as by the global criteria developed in
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the ASHRAE standard 55 and EN 15251; all three comfort criteria were developed using
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datasets based on field surveys in NV buildings.
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Shifting of thermal satisfaction toward mixed-mode buildings in warm climate
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In thermal adaption, it was argued (Humphreys 1974; McIntyre 1980) that people living
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in warm climate might prefer a slightly cool environment whereas those who were used
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to cold weather might favor more of a slightly warm environment. Hwang et al. (2009b)
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observed that, after being continuously exposed to a warm-to-hot microclimate during
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summer months in the NV classroom, Taiwanese students experienced a shift in their
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optimal sensation from thermally neutral (0) to slightly cool (-1) as manifested in their
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TSV. The tendency of favoring a slightly cool environment among those who lived in a
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hot-and-humid weather was also reported in other studies, e.g., Andamon et al. (2006)
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and Feriadi and Wong (2004). While the shifting in the thermal preference as discussed
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here was commonly assumed in the studies of thermal comfort in the NV spaces,
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whether a similar assumption could be applied in the buildings employing mixed-mode
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ventilation would require further evaluation, as in the mixed-mode classroom the
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experience of hot weather was lessened by using the AC.
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An effective means to evaluate the shifting in the thermal preference was to
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compare the percentage of thermal satisfaction from the TSV (ptsv) with those from the
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TCV (ptcv) and TAV (ptav). In this evaluation, the ptsv was first defined as the TSV cast on
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the central three grades (-1, 0, and +1), a general approach commonly adopted in
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TSV-based evaluation of thermal satisfaction. These votes represented a preference of
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the students for a neutral thermal sensation. Then the ptsv was re-defined by pooling the
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votes cast on the grades of -2, -1, and 0, representing a preference for a cooler sensation.
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To verify the tendency of change in the thermal preference among the students with
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respect to their thermal sensation, these percentages were separately compared to the
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percentages of TCV cast on the “slightly comfortable”, “comfortable”, and “very
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comfortable” categories (ptcv) as well as to the percentages of TAV voted on the
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“acceptable” category (ptav). Fig. 3 reported the box-and-whisker distribution of the
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deviations of ptsv from ptcv and ptav as affected by the top when different assumptions of
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preference in thermal sensation were adopted. As the results show, overall the variation
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between the ptsv for TSV (-1, 0, +1) and the ptcv or ptav was significantly greater than the
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level derived when the TSV (-2, -1, 0) was considered the votes of satisfaction. When
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the TSV (-1, 0, +1) was assumed to represent thermal satisfaction, the average difference
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between the ptsv and the ptcv/ ptav in hot condition (top > 27°C) was in general greater than
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their counterpart calculated for the mild condition (top < 27°C) by approximately 10%,
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suggesting a shift in the distribution of acceptable or comfortable thermal perception
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toward the cool side of the thermal sensation scale during the hot days. The above
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analysis also demonstrated that the students in a mixed-mode classroom had the same
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tendency of preference on a thermal environment as those situated in a NV classroom.
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Modeling of thermal perception
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In Hwang et al. (2009b), a best likelihood probit model was developed by means of
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logistic regression for estimating the percentage of thermal dissatisfaction in TSV, TCV,
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and TAV due to the thermal environment being warm. The logistic regression employed
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was mathematically expressed as:
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probit ( phot )  a  b  top
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(6)
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Table 6 listed the results of the same regression analysis using the responses of the
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students in TSV, TCV, and TAV in this study as well as the estimated upper limits of
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comfort zones for the 90% and 80% acceptability. As the results show, the upper bounds
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of the top corresponding to different thermal perceptions ranged between 28.1 and
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28.4°C for the 90% acceptability and between 29.3 and 29.7°C for the 80% acceptability.
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The limits developed by the observations in this study were slightly lower than the
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values recommended by Hwang et al., with the difference being in the range of
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0.0-0.3°C and 0.3-0.7°C for the 90% and 80% acceptability, respectively.
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To further compare the students’ thermal perception with the adaptive thermal
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comfort criteria established in the ASHRAE Standard 55 and EN 15251, the students’
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answers on the TAV-based thermal acceptability in the mixed-mode classroom were
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grouped into different acceptability levels and distributed by the top, tom and trm on the
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adaptive thermal comfort chart demonstrating the thermal acceptability zones projected
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by the ASHRAE Standard 55 adaptive comfort model (Fig. 4) and on the chart
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indicating the acceptability categories projected by the EN 15251 model (Fig. 5).
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Overall, the development of the students’ thermal perception tracked the predictions by
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the ASHRAE 55 and the EN 15251 in most of the top measured in this study. However,
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for the top close to and above 30°C, the acceptability observed in this study was lower
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than the level predicted by the ASHRAE Standard 55, and the deviation increased when
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the benchmark referenced in comparison was the prediction made by the EN 15251
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model. The under-representation for the observations of acceptability made in our study
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by both the ASHRAE and the EN models was possibly attributed to a reduced tolerance
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of the students to high temperature, since for these students the AC was readily available
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as a means to alleviate the hot discomfort. These results clearly indicated that the change
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in thermal comfort of indoor occupants was not only driven by climatic factors but also
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influenced by socioeconomic status of the occupants. These results suggested that, when
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attempted for local application, the adaptive thermal comfort models developed by a
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global or regional database should first receive validation using a dataset of locally
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conducted survey results.
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Modeling of fan and air-conditioning usage
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Fig. 6 demonstrated the alteration in the proportion of time in the school classroom
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employing a mixed-mode ventilation when the fans or AC was actively used in response
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to the change in the ambient temperature. The students’ adaptive behaviors were
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significantly influenced by the outdoor temperature, and the influence could be
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interpreted by a sigmoidal relationship between the behavior and the temperature. Nicol
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(2001) proposed a stochastic algorithm for modeling the thermal comfort-driven
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adaptive (TCDA) behavior, and the algorithm was applied in various studies (Andersen
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et al. 2009; Nakaya et al. 2008; Nicol and Humphreys 2004; Rijal et al. 2008; Rijal et al.
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2009; Tuohy et al. 2009) to characterize the adaptive behaviors of the occupants to stay
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in control of the indoor climate. To quantitatively illustrate how the students
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participating in this study used various environmental controls as a strategy of thermal
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adaption, the survey data were analyzed following the Nicol’s algorithm and fitted to
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generate logit models that described the probability of the fans (pfan)/AC (pAC) being
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turned on as a function of the outdoor temperature (tout):
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logit( p fan )  log(
p fan
1  p fan
)  0.88  tout  25.6 R 2  0.88
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(7)
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logit( p AC )  log(
p AC
)  0.97  tout  34.2 R 2  0.86
1  p AC
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(8)
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It has been observed that in circumstances where an adaptive action could have
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some adverse impact the occupants might tolerate thermal discomfort to a certain degree
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before taking that action (Humphreys 1974). The fee-for-service mechanism for
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controlling the AC use in a mixed-mode classroom would be an example attesting to this
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observation, as the use of AC led the students to shoulder up excess energy expenditure.
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The concern with the cost from the AC use could be viewed as a constraint that drove
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the students to postpone the use of AC as an adaptive strategy. Fig. 7 shows the
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probability of active AC use under the TCDA approach in the fee-for-service energy
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management versus the probability of use under a temperature threshold approach.
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When the TCDA approach inherent in the fee-for-service control of AC was applied in
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the energy management, the probably of the AC running in the classroom was much
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lower than the level anticipated for when the temperature threshold approach was
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applied, in which the AC was only turned on at a specific temperature. The
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fee-for-service mechanism apparently provided a better choice in this case as far as a
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balance between the energy conservation and the occupants’ thermal comfort was
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concerned.
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However, compared to the fee-for-service mechanism, the temperature threshold
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approach might be more advantageous to the management when the level of energy
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consumption needed to be controlled with certainty and could not accommodate an
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unanticipated variation in energy use as a result of the users’ decision. A couple of
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examples attesting to this scenario would be when the energy cost in the buildings was
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not shared by the users or when the cost had to be shared by estimation prior to the
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actual consumption of energy (e.g. sharing the energy cost via the tuition fees for the
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students). In these cases, the users might be less concerned with the level of energy
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consumption, and the temperature threshold approach would provide a mechanism to
413
prevent excess, unnecessary energy use. The fee-for-service and temperature threshold
414
mechanisms could indeed be applied jointly in energy control for the school buildings if
415
an appropriate management program can be devised, with the temperature threshold
416
management in this case serving to alarm the users the excess use of energy.
417
418
23
419
Conclusions
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421
In Taiwan, the fee-for-service mechanism is a popular approach in control of the AC use
422
and for promotion of the thermal comfort in the classroom owing to its user-friendly and
423
economic attributes. A field survey was conducted to evaluate the student’s thermal
424
satisfaction and adaptive behavior in a mixed-mode school classroom in Taiwan where
425
the AC was operated under the fee-for-service control. The key findings included:
426
The most frequently used mechanism of environmental control was to jointly open
427
the windows and run the fans (64%), which was followed by opening the windows alone
428
(25%) and a joint use of the fans and AC (11%). The mean top in the period of using the
429
fans and AC was 30.3°C, 1.3°C higher than the level (29.0°C) observed when using the
430
windows and fans for ventilation and 5.3°C higher than that (25.0°C) observed when the
431
windows were used alone. There was 11-33% of the class hours when the top exceeded
432
the acceptable range of the 80% thermal acceptability described in the ASHSRAE
433
Standard 55 or the Category II thermal zone in the EN 15251.
434
Questionnaire surveys confirmed that the students in a mixed-mode classroom
435
shared the same thermal preference as those would be expected in an NV classroom. The
436
estimated upper limits, derived from the student’s responses in the TSV, TCV and TAV,
437
occurred in the range of 28.1-28.4°C for the 90% acceptability and 29.3-29.7°C for the
24
438
80% acceptability. The results also revealed that the fee-for-service mechanism served as
439
a constant reminder to the students of the cost using the AC, facilitating a constraint on
440
the AC use and a higher threshold temperature by which the AC was activated. The
441
fee-for-service mechanism provided a better choice in energy control compared to the
442
conventional temperature threshold-based approach as it balanced between the energy
443
conservation and the occupants’ thermal comfort. When the level of energy consumption
444
in the school buildings needs to be controlled with certainty, the fee-for-service and the
445
temperature threshold mechanisms may be jointly applied, if an appropriate
446
management program can be devised, with the temperature threshold management
447
serving to alarm the students the excess use of energy.
448
449
Acknowledgments
450
451
The funding to this research was provided by the National Science Council of Taiwan in
452
grant under the project number NSC-101-2221-E-239-035 and is sincerely
453
acknowledged.
454
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Figure captions
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Fig. 1 Distribution of operative temperature in the school building employing mixed
534
-mode ventilation during the course of this study (April 1 to June 30, 2011)
535
superimposed with ranges of thermal acceptability as projected by ASHARE
536
Standard 55 and EN 15251 adaptive models
537
Fig. 2 Distribution of operative temperature by relative humidity (expressed in humid
538
ratio) in the school building employing mixed-mode ventilation on thermal
539
comfort chart of ASHRAE Standard 55 superimposed with elliptic groups of
540
observations for the students’ use of different environmental controls
541
Fig. 3 Shifting of thermal preference among the students in response to change in
542
operative temperature (top). Thermal preference was determined as percentage of
543
thermal satisfaction in thermal sensation vote (ptsv), thermal comfort vote (ptcv),
544
and thermal acceptability vote (ptav), and shifting of preference was expressed as
545
variation between ptsv and ptcv and between ptsv and ptav. ptsv was defined as
546
thermal sensation vote (TSV) cast on -1, 0, +1 (∑(-1, 0, +1)) of the 7-point TSV
547
scale when neutral sensation was preferred or as TSV cast on -2, -1, and 0
548
(∑(-2,-1, 0)) when cooler sensation was preferred. ptcv and ptav were defined as
549
thermal comfort vote (TCV) cast on -1 and +1 of the 6-point TCV scale and
550
thermal acceptability vote (TAV) cast on +1 of the dichotomous TAV scale
30
551
respectively.  ptsv − ptcv and  ptsv − ptav were the absolute values from
552
subtracting ptcv and ptav from ptsv respectively
553
Fig. 4 Thermal acceptability in the school building employing mixed-mode ventilation
554
grouped in different acceptability levels and distributed by operative temperature
555
and monthly mean ambient temperature. Survey observations were presented in
556
symbols and acceptability zones projected by ASHARE Standard 55 adaptive
557
comfort model were presented in parallel lines
558
Fig. 5 Thermal acceptability in the school building employing mixed-mode ventilation
559
grouped in different acceptability levels and distributed by operative temperature
560
and monthly mean ambient temperature. Survey observations were presented in
561
symbols and acceptability categories projected by EN 15251 adaptive comfort
562
model were presented in parallel lines
563
Fig. 6 Change in the proportion of time using fans or air-conditioning in the school
564
building employing mixed-mode ventilation in response to change in the ambient
565
temperature. Results from on-site monitoring were presented in symbols and
566
projections from likelihood logit model on thermal comfort-driven adaptive
567
behavior were presented in parallel lines
568
Fig. 7 Probability of active air-conditioning (AC) use under thermal comfort-driven
569
adaptive (TCDA) approach in fee-for-service energy management versus under
31
570
temperature threshold approach
32
571
Table titles
572
573
Table 1 Thermal comfort survey questionnaire used in evaluating perceptions of
574
students toward thermal conditions in the classroom in relation to
575
fee-for-service energy control
576
577
Table 2 Indoor climatic parameters monitored in this study and equipments used for
monitoring
578
Table 3 Thermal acceptability categories defined in ASHRAE Standard 55 and EN
579
15251 for requirements of adaptive comfort in buildings and boundaries
580
established for each category as expressed in optimal operative temperature of
581
thermal comfort indoors (tcomf)
582
Table 4 Summary for percentages of hours when the classroom was occupied and
583
indoor operative temperature (top) was over upper bounds of adaptive thermal
584
comfort criteria established in ASHRAE Standard 55, EN 15251, and Hwang et
585
al. (2009b)
586
Table 5 Distribution in frequency of the students’ response toward thermal status in the
587
classroom as in thermal sensation vote (TSV), thermal comfort vote (TCV), and
588
thermal acceptability vote (TAV)
589
Table 6 Results of probit analysis using responses of the students in thermal sensation
590
vote (TSV), thermal comfort vote (TCV), and thermal acceptability vote (TAV)
33
591
as well as the estimated upper limits of thermal comfort zones for 90% and
592
80% acceptability as expressed in operative temperature (top)
34