THERMAL COMFORT ANALYSIS OF BUILDINGS USING THEORETICAL AND ADAPTIVE MODELS Hélder Silva Almeida

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1 THERMAL COMFORT ANALYSIS OF BUILDINGS USING THEORETICAL AND ADAPTIVE MODELS Hélder Silva Almeida Lisbon, October Introduction EXTENDED ABSTRACT Nowadays construction is increasingly constrained by a set of functional requirements that it must guarantee, it results from higher standards of living of today s societies. Among this group of demands, thermal comfort gains importance. We must bear in mind that changes in the thermal characteristics of indoor environments imply a bigger biological stress of their occupants, who need to replace the heat balance between the organism and the environment that surrounds it. This effort brings negative consequences for their health [1]. On the other hand, to the guarantee of the characteristics of indoor thermal comfort we must associate energy consumption for HVAC systems (25% of the total energy used in buildings which represents 17% of national primary energy [2]). This raises the issue of environmental sustainability. In this sense, regulatory documents have been developed which aim, through the design constraints, limiting the energy requirements of heating and cooling provided by buildings - RCCTE [3]. It is in this context that the analysis of indoor thermal comfort in free-running buildings assumes a large importance as a means of assessing the response of buildings to outdoor characteristics without resorting to HVAC systems. Buildings that under free running mode have better thermal comfort indices will indicate, in most cases, a lower energetic effort to replace the internal conditions of comfort. Therefore, in this study we seek to evaluate the thermal comfort of buildings with different construction solutions representative of the progress of thermal regulation in Portugal, analyzing some of the factors conditioning the indoor thermal characteristics, such as building orientation, layout and activation rate shading systems, geographical localization and position of the floor in height. This study is conducted based upon a theoretical methodology and an adaptive analysis of thermal comfort in buildings. 2. Analysis of thermal comfort Depending on the thermal comfort of heat balance between the organism and the environment, there are several factors, physiological and environmental,which constraint this state, for example: the body's metabolic rate (developed physical activity), thermal resistance of clothing used, air temperature, relative humidity, air velocity and surfaces temperature [4]. Thus, since the beginning of last century, several studies were conducted in an attempt to translate the combined outcome of factors affecting the thermal comfort in buildings into a single parameter/index, allowing then to set ranges of comfort for this same parameter. The process of 1

2 defining the thermal comfort index has followed mainly two different approaches: theoretical and adaptive. The analytical approach is characterized by the development of studies that use climate chambers that are adjusted to various environmental factors (temperature, air velocity, surface temperatures and humidity), proceeding to the registration of thermal sensations experienced by individuals who are inside facing different combinations of environmental variables. The adaptive approach, on the other side, is based on the definition of criteria of comfort in the course of field researches. In these studies the environmental variables are measured directly in real environments where the occupants of the buildings are involved in their habitual activities, registering their thermal sensations afterwards Theoretical approach The first comfort indexes derived from extensive laboratory campaigns (climate chambers) integrated the effect of varying air temperature, relative humidity and air velocity, especially the effective temperature index (effective temperature) (ET) developed by Houghten and Yaglou (1923) referred to in [5]. This index has undergone several developments related to the integration of other personal and environmental variables in their calculation process, highlighting the effects of clothing and the thermal radiation of the surfaces proposed by Yaglou and Miller in 1925 and Vernon in 1932, respectively, specified in [5]. With the integration of this last factor comes a new index of thermal comfort, CET (corrected effective temperature). Winslow, Gagge and Herrigton in the late 30s of the 20 th century also attempted to translate the effects of radiation surrounding thermal comfort conditions, they then proposed a new thermal comfort index called operative temperature (OT), cited in [4]. In 1935, Missenard, mentioned in [6], presents the resulting temperature parameter (RT) that was obtained by processes very similar to the ones of effective temperature and reflects the thermal sensation of users after a period of adaptation to environmental conditions in climate chambers. Following the developments in scientific research in this area and looking to quell some of the problems of underestimation and blistering of the effects of humidity in the effective temperature (ET), some have proposed a new index of effective temperature - New Effective Temperature (ET *) [7]. However, one of the indexes of analysis of thermal comfort in buildings more publicized matches the predicted mean vote (PMV) developed by Fanger [8] and adopted by regulations ISO 7730:2005, ASHRAE and EN : This index is based on the equation of heat balance (2.1) defined by the same author and in the assumption that thermal comfort corresponds to a rate of thermal load on the body (S) void. (2.1) Where: S - thermal load on the body (W/m 2 ); M-W - metabolic heat production (W/m 2 ); Q sk heat loss through the skin (W/m 2 ); Q res heat loss due to respiration (W/m 2 ). In the aftermath of his work, Fanger [8] defined a scale of thermal sensation with seven levels (3 - hot, 2 - warm, 1 - Slightly warm, 0 - neutral, -1 - Slightly cool, -2 - cool, -3 - cold), translating, through it, the 2

3 degree of discomfort associated with the different combinations of environmental and personal variables tested in climate chambers. Based on the relation between the thermal sensation experienced by users in controlled environmental chambers and the thermal balance equation (2.1), Fanger [8] calculated the PMV index through the following expression: (2.2) In addition to this index, Fanger [8] proposed another indicator that, based on this one, estimated the predicted percentage of dissatisfied - PPD. The PPD index calculation is done using the following equation: (2.3) The relation established between these two indexes can be expressed graphically (see Figure 2.1). Observing it, we verify that it is not possible to achieve a zero value for the predicted percentage of dissatisfied, because to the index value 0 of the PMV index corresponds a predictable minimum percentage of dissatisfied of 5% Adaptive approach Fig Relation between PMV and PPD The recognition that thermal sensations result not only from physiological parameters but also from psychological ones, such as the expectation of each user in relation to the thermal conditions inside the building and towards the opportunity of influencing them (by opening and closing windows, installing air conditioning equipment and controlling shading mechanisms). This acknowledgment is the engine of this line of research, supported by the record of thermal sensations directly in places occupied by people [9]. Recording the execution of several works based on observing people during their day-to-day lives in ordinary buildings, highlighting the works published by Humphreys (1975) [10] Auliciems (1981) [11] and De Dear (1998) [12], where it is tacit that users are not passive agents in relation to the thermal conditions of the buildings that they occupy, since they promote actions that aim to achieve the conditions that each consider appropriate in terms of thermal comfort [13] (change of clothing, posture, physical activity, manipulation of windows and shading devices, change of location within the building). Humphreys (1979) [14] demonstrated, through this approach, the existence of a strong correlation ( ) between the indoor temperature neutrality (θ n ) and the mean monthly 3

4 outdoor temperature ( equation (2.4) this correlation: ), especially in buildings under free running, translating into the following (2.4) Other authors showed adaptive relations between the interior temperature of comfort and the monthly average temperature outside, both general, as was the case Aulicems (1981) [11] - Equation (2.5) - De Dear (1998) [12] - equation (2.6) - and private, as was the case of Nicol and Roaf [15] to the territory of Pakistan - equation (2.7). Where: - globe temperature; - mean monthly outdoor temperature from the previous month. (2.5) (2.6) (2.7) 3. Methodology Taking into account different methods of analysis of the provided thermal comfort, we opt in this study for the use of both approaches to evaluate thermal comfort, analytical and adaptive. It is important to refer that we utilized software that allows the dynamic simulation of thermal behavior of buildings - EnergyPlus - to obtain the results for this paper. The analysis is divided into two periods corresponding to conventional heating and cooling seasons RCCTE defined in [3]. Three constructive solutions were evaluated for each weather file (Lisbon - climate zone I1, Porto - I2 zone - and Bragança - Zone I3) representing the current application of thermal regulation (L.1 solutions - Lisbon - P.1 - Porto - and B.1 - Bragança), the previously existing one [16] (L.2, P.2 and B.2) and the constructions which date from before the first thermal regulation of buildings in Portugal (L.3, P.3 and B.3) Theoretical model adopted - Methodology Fanger (PMV) The analytical methodology adopted in this work is based upon the model of Fanger [8], establishing, for each hour of study periods, the index value of PMV. We applied the potential of the EnergyPlus software to calculate this index. As a standard for comfort, we establish that all periods whose PMV index varies between -0.5 and 0.5 are considered periods of comfort, since they correspond to PPD indices below 10% - more than 90% of comfort responses given by the occupants (see Figure 2.1) Adaptive model adopted As mentioned in Section 2.2 there are several expressions for calculating the comfort temperature. Thus, we decided on adopting the adaptive models proposed by ASHRAE and EN 4

5 15251:2007 regulations, whose model was developed by SCATS model (Smart Controls and Thermal Comfort). The assessment made by these models implies the calculation of internal comfort temperatures based on the daily and monthly average temperatures outside, comparing them then with the interior comfort temperatures Adaptive model - ASHRAE The evaluation of thermal comfort proposed by this model focus on the calculation of indoor monthly comfort temperature following the outdoor monthly average temperature translated by the expression (2.6) which compares the indoor temperatures. Thus, and following the ASHRAE RP-884 project [17], intervals were set that guaranteed the acceptability of indoor thermal conditions by at least 90% of occupants of buildings in relation to comfort temperatures calculated monthly by the equation (2.6). These intervals corresponded to a range of 2.5 o C around the comfort temperature [18] Adaptive model - EN 15251:2007/Study SCATs Given that the adaptive model proposed by EN 15251:2007 was built on the results of the SCATs study developed in European territory, it is proper to use this model to evaluate the thermal comfort of buildings in Portugal. This model proposes the adaptive equation (3.1), for the Portuguese territory in particular, to calculate daily the interior comfort temperature (T c ). We calculate it based on the value of the running mean outside temperature (T RM ) - equation (3.2). Where: - running mean outside temperature of the day n ( o C); - running mean outside temperature of the day n-1 ( o C); - mean daily outdoor temperature of the day n-1 ( o C). (3.1) (3.2) For ranges of comfort, the SCATs study, which is the basis for preparation of the adaptive model of EN 15251:2007, proposes a differentiation of buildings depending on building types and not on the quality of the buildings construction [19]. It is considered therefore a range of comfort of 3 o C for constructive solutions representative of the implementation of the two regulations that existed in Portugal, and 4 o C for the remaining ones Parameters characterizing the periods of discomfort In this paper, we evaluate the number of hours with discomfort as well as their percentage distribution by daily periods of analysis (0-6h, 6-12pm, 12-18h and 18-24h). We also measure the degrees of discomfort above or below the ranges of comfort (adaptive models) using indicators of hour-degrees of discomfort ( o C.h) and mean superheat or mean supercooling ( o C) of the discomfort periods. 5

6 4. Presentation and analysis of results Regarding shading systems influence we can observe that, during the cooling season, and especially in the middle floors, the adoption of exterior shading systems lead to substantial reductions in both the number of hours with discomfort or the discomfort level, achieving, with smaller areas of activation of exterior devices, values very close to those obtained by the interior systems with higher rates of activation - best use of natural lighting - as recorded in table 4.1, used as an example, for the weather file Lisbon and solution L.1. Kind Table Comfort indicators, cooling season, the intermediate floor, South orientation, L.1 Método ASHRAE SCATs PMV Shadowing Active area Nº of hours with discomfort Degrees-hour ( o C.h) Nº of hours with discomfort Degrees-hour ( o C.h) Nº of hours with discomfort Ext. 70% % Int. 70% % Without shadowing The building s orientation is also evaluated in this study. During the cooling season, East and West orientations maximize the number of hours with discomfort and the value of degree-hours of discomfort in the three climatic files and in the various constructive solutions analyzed in this study, as shown in Figure 4.1 relating to the weather file of Bragança. Fig Comfort indicators in relation to the orientation of the building, cooling seasson, without shading, climatic file of Bragança, B.1 These results are associated with an unfavorable distribution of windows in these directions, through the facades of the buildings, leading to an increase in periods of distress throughout the day by increased solar gains (Figure 4.2). In each of the constructive solutions, the results for the top floor are more worrying, registering a greater extension of the periods of discomfort and less favorable values for the comfort level of these periods (Figure 4.1). In Figure 4.1, we find less differences between the numbers of hours of discomfort in the four orientations of the top floor, when compared to the intermediate level - increase in power savings due to the opaque surroundings - observing, then, the diminishment of the influence of the orientation of the building in the comfort indicators for the top floor. 6

7 Fig Distribution of the hours of discomfort throughout the periods of the day, intermediate floor, weather file of Bragança, B.1, outside shading 70% active area In all three weather files, the latest construction solutions for the intermediate floor (greater thermal insulation of the involvement) score more severely on the number of periods of discomfort and comfort levels associated with these (degree-hours of discomfort and medium overheating), a tendency that may be related with the greater difficulty of dissipation the heat inside (more insulated areas) that contributes to the increase of the indoor temperature. On the top floors we notice this trend s reversal, as the latest construction solutions show best indicators of comfort during the cooling season, as Porto s weather file in Figure 4.3 shows. Fig Indicators of thermal comfort, cooling season, weather file of Porto, East orientation, exterior shading 70% active area Finally, for the cooling season, the Porto s weather file has the most favorable results for the various comfort indicators; nonetheless there are some occasional uncomfortable situations that emerge from the SCATs analysis of the adaptive method, depending on some very specific conditions. This fact seems to indicate the chance of buildings running under free mode almost permanently. On the other hand the climatic files of Lisbon and Bragança seem to provide less positive values of the indicators of discomfort, denoting, however, possibilities for exploitation of the buildings under free range mode s potential (see Figure 4.4). Moreover, we noticed that although Lisbon s weather file tends to show 7

8 higher values for the number of hours of discomfort, it is the weather file of Bragança that presents a bigger discomfort during the periods of discomfort. Fig Indicators of thermal comfort during the cooling season, depending on the weather file, West orientation, exterior shading 70% active area As for the heating season, most of the constructive solutions show sharp restrictions in the buildings under free range. We noticed that for the three methods of analysis, the directions west and south presented the most significant results in the number of hours with discomfort (Figure 4.5). However, the Western orientation leads to significantly higher levels of discomfort for these periods than other orientations, we think that it may possibly be due to the reduction of solar gains during the heating season relating to the unequal distribution of windows (Figure 4.5). Fig Indicators of comfort depending on the orientation, heating season, weather file Lisbon, L.1 On the other hand, the results for the top floor show more onerous indicators of discomfort compared with the middle floor, noticing the influence of heat losses introduced by the coverage in indoor conditions of thermal comfort (see Figures 4.5 and 4.6). There is also a greater homogeneity during the extension of discomfort periods in what concerns the results of different orientations of the covering floors. 8

9 The regulatory evolution reflects an improvement in the results for the heating season, noting that the latest solutions (more insulated surroundings) tend to have more favorable comfort indicators, reflecting an increased resistance to the dissipation of interior gains (Figure 4.6). Fig Indicators of thermal comfort during the heating season, Porto s weather file, West orientation, no shading Comparing the results of the three weather files (climate zones - I1, I2 and I3), Lisbon s climatic file solutions are the ones that provide less adverse results, distancing themselves from the solutions found for the climatic files of Porto and Bragança (Figure 4.7 ). These climate files present extensions of the periods of discomfort relatively close, although the period level of discomfort is substantially higher for the weather file of Bragança, reaching values of accumulated degree-hours of discomfort very significant, as illustrated in Figure 4.7. Fig Indicators of thermal comfort during heating season, depending on the weather file, West orientation, no shading The results presented above seem to point to serious constraints on the operation of free-running mode buildings during the heating season, limiting this incidence to the initial and final months of the heating season, as shown in Figure 4.8. However with the evolution of thermal regulation, there is a progressive adaptation of constructive solutions to the weather conditions outside, helping this way to reduce energy requirements to heat the buildings. 9

10 Fig Indicators of thermal comfort- heating season months, orientation South, no shading, Porto weather file, intermediate floor, P.1 This study only presents some of the results, so we advise our readers to look at the work that underpins this article. 5. Conclusions This work allowed the detailed analysis of indoor thermal comfort, concluding on the potential demonstrated by the various constructive solutions of a correct use of the free running operating system of buildings during the cooling season. This was accomplished by taking advantage of the comfort ranges proposed by the methods of analysis of thermal comfort and managing to obtain energy consumption reduction in HVAC systems. For the cooling season, the shading devices play an important role in implementing the conditions that lead to indoor thermal comfort parameters, as well as the distribution of windows, since larger areas of windows oriented East and West contribute to the augmentation of solar gains which are translated into increased interior temperatures. On the other hand, the heating season, for these three weather files, presents unfavorable comfort indicators operating under free-running mode buildings. There are, in most months of the cooling season, high values for the extension of discomfort periods and comfort indicators that are intended to reflect the level of discomfort associated with these periods. For both heating and cooling seasons, covering floors tend to aggravate the indicators of thermal comfort, therefore we observe in the cooling season, an enhancement in heat gain due to the presence of opaque surfaces (cover) leading to higher internal temperatures. During the heating season, we notice an increase of energy losses in relation to the intermediate floor, which contributes to the reduction of indoor temperatures. The higher gains and losses of heat in the top floors during cooling and heating seasons, correspondingly, mean that there is a decrease in the influence of the building s orientation and shading systems layout in the results of the indicators of thermal comfort. References [1] Frota, A. B.; Schiffer, S. R.; Manual do Conforto Térmico, Studio Nobel, São Paulo, 1987; [2] Eficiência Energética nos Edifícios, Direcção Geral de Energia - Ministério da Economia, Fevereiro 2002; 10

11 [3] RCCTE - Decreto-Lei n. o 80/2006, de 4 de Abril de 2006; [4] Moret Rodrigues, A.; Canha da Piedade, A.; Braga, A. M.; Térmica de Edifícios; Orion; Amadora; 2009; [5] Ruas, A. C.; Avaliação de Conforto Térmico - Contribuição à aplicação prática das normas internacionais; Faculdade de Engenharia Civil da Universidade Estadual de Campinas, Campinas, 2001; [6] Monteiro, L. M.; Conforto térmico em espaços abertos e temperatura equivalente de percepção; Faculdade de Arquitectura e Urbanismo da Universidade de São Paulo, São Paulo; [7] ANSI/ASHRAE Standard Thermal Environmental Conditions for Human Occupancy, American Society for Heating, Refrigerating and Air-Conditioning Engineers, Atlanta, 2004; [8] Fanger, P. O.; Thermal Comfort, McGraw-Hill, New York, 1972; [9] Brager, G. S.; De Dear, R.; Climate, Comfort, & Natural Ventilation: A new adaptive comfort standard for ASHRAE Standard 55; University of California, Berkeley, 2001; [10] Humphreys, M.A.; Fields study of thermal comfort compared and applied; Building Research Establishment (BRE), Garston, 1975; [11] Auliciems, A.; Towards a phsycho-physiological model of thermal perception; Internacional Journal of Biometeorology, 25, pp , 1981; [12] De Dear, R. J.; A Global database of thermal comfort field experiments; ASHRAE Transactions 104, pp , 1998; [13] Nicol, F.; Pagliano, L.; Allowing for Thermal Comfort in Free-Running Buildings in the New European Standard EN 15251; [14] Humphreys, M. A.; The influence of season and ambient temperature on human clothing behavior; Indoor Climate, Danish Building Research, Copenhagen, 1979; [15] Brager, G. S.; De Dear, R. J.; Thermal adaptation in the built environment: a literature review; Energy and Buildings 27, pp , 1998; [16] RCCTE - Decreto-Lei n. o 40/90, de 6 de Fevereiro de 1990; [17] De Dear, R,; Brager, G.; Cooper, D.; Developing an Adaptive Model of Thermal Comfort and Preference; ASHRAE, 1997; [18] De Dear, R.; Brager, G. S.; The adaptive model of thermal comfort and energy conservation in the built; Biometeorol 45, pp , 2001; [19] Nicol, F.; Humphreys, M.; Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN 15251; Building and Environment 45, pp ,

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