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A statistical approach for the evaluation of thermal and visual comfort in free-running buildings
Energy and Buildings 47 (2012) 402–410
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A statistical approach for the evaluation of thermal and visual comfort in free-running buildings Fabio Sicurella a,∗ , Gianpiero Evola a , Etienne Wurtz b a b
LEPMI – CNRS, 73376 Le Bourget-Du-Lac, France LEB – CEA – INES, 73376 Le Bourget-Du-Lac, France
a r t i c l e
i n f o
Article history: Received 19 March 2011 Received in revised form 22 September 2011 Accepted 12 December 2011 Keywords: Statistical indicators Thermal comfort Visual comfort Warm season Windows
a b s t r a c t In recent years, the study of indoor environmental comfort during the warm season has been one of the most attractive and hard tasks for architects and energy designers. Nowadays, thanks to the available high-performance utilities, the dynamic energy simulation of a building is relatively easy. Nevertheless, since it should simultaneously account for thermal, visual and air quality issues, a global approach, often neglected, becomes necessary. In the present work, an approach based on simple indicators calculated on a statistical basis will be presented; it can be useful for the simultaneous evaluation of the indoor thermal and visual comfort on a more comprehensive perspective, and it can be applied in any building energy analysis where a comparison between different solutions or strategies is required. At the end of the paper this approach is tested on a simple case study in order to show how the approach can be used to evaluate the influence of the size and the typology of a window on indoor comfort. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Almost thirty years ago the PMV-PPD model for thermal comfort proposed by Fanger [1] had a wide scientific consensus so that it was included, several years later, in the ISO Standard 7730 [2]. This approach, based on a steady-state energy balance on the human body, allows the prediction of thermal sensation and comfort satisfaction of the human body as a function of six parameters related to the indoor environment (internal temperature, air velocity, humidity, mean radiant temperature) and to the occupants (activity and clothing), without any correlation with the external environmental conditions. This model, developed by using the results of interviews carried out under controlled micro-climatic conditions (typical of buildings provided with HVAC systems), is not suitable to manage the transient state that occurs, for instance, in naturally ventilated buildings, in buildings without HVAC systems or where occupants vary their behaviour and activity. This means that for most bioclimatic buildings as well as for a large number of renewed buildings Fanger’s approach might not be suitable. On the other hand, in the same years the adaptive model proposed by Nicol and Humphreys [3] stated that people’s interaction with the external and internal environment allows a range of
∗ Corresponding author. E-mail addresses: [email protected], [email protected] (F. Sicurella), [email protected] (G. Evola), [email protected] (E. Wurtz). 0378-7788/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2011.12.013
thermal comfort conditions which is wider than that admitted by a steady-state model. Actually, people can react to changes in the environment by taking appropriate actions or by changing their attitudes, in order to restore a comfortable condition even if the environment where they are placed has undergone appreciable changes. de Dear and Brager [4] also underlined that people who live or work in naturally ventilated buildings, where they are able to open windows, get used to thermal variations reflecting local climatic patterns. By analysing a great number of surveys conducted world-wide on free-running buildings, Nicol and Humphreys [5] found a clear correlation between the comfort operative temperature and the running mean outdoor temperature measured over the previous days. As a consequence, they stated that thermal comfort in free-running buildings can be assessed just as a function of the indoor operative temperature, so neglecting all the other parameters accounted for in Fanger’s model, which would have a minor importance. Then, while Fanger’s approach intrinsically postulates the need of a system to provide and keep optimal thermal conditions inside the building, the adaptive approach just defines a range of temperatures in which an occupant can find his own comfort without the aid of any air-conditioning system, provided that he is free of adapting his behaviour and of operating on the openings to deploy natural ventilation. When studying low energy demand buildings, the adaptive approach appears much more appropriate, since no HVAC is postulated and a link is created between human behaviour, its interaction
F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
Nomenclature E Eover Eunder FOT FTC FTD FD FVC ITD IVD Tover Tunder Top Tout Trm
illuminance (lux) upper limit of the visual comfort range (lux) lower limit of the visual comfort range (lux) frequency of the operative temperature (%) frequency of thermal comfort conditions (%) frequency of thermal discomfort conditions (%) fluctuation of thermal discomfort (◦ C) frequency of visual comfort conditions (%) intensity of thermal discomfort (◦ C h) intensity of visual discomfort (lux h) upper limit of the thermal comfort range (◦ C) lower limit of the thermal comfort range (◦ C) operative temperature (◦ C) outdoor air temperature (◦ C) running mean outdoor temperature (◦ C) time (h)
with the environment and, as a consequence, the building energy demand. The importance of this approach has increased in the last ten years so that it was first included in the ASHRAE standard 55 [6] and more recently in the EN standard 15251 [7]. The latter provides, among other things, the acceptable indoor temperature ranges for buildings without mechanical ventilation systems. A comprehensive review of the approaches available to study thermal comfort is reported in [8]. Another fundamental aspect of the environmental comfort is the correct use of daylight. The definition and the quantification of visual comfort are less standardised than thermal comfort, since it depends on the available external daylight, on the glazing and screens that “filter” it, on the indoor environment (optical characteristic of walls) and, of course, on the visual task. The EN Standard 12464-1 [9] establishes the fundamental rules for artificial lighting in indoor work places and tackles the glare issues. But, up to now, no rules and suggestions have been given concerning the optimal values of daylight illuminance, its uniformity and glare; just a qualitative approach encouraging the integration between natural and artificial lighting is reported. The recent EN Standard 15193 [10] introduces a new indicator to evaluate energy consumption for lighting, which also includes the contribution of daylight. This approach is quite innovative since it allows the evaluation of lighting control logics based on the integration with the daylight for energy savings. Nevertheless, the daylight availability is still assessed through the calculation of the daylight factor, hence with a static approach, and cannot account neither for the real potential of natural lighting nor for the efficacy of dynamic shading devices. This lack is misleading, since a precise evaluation of the daylight availability is fundamental to correctly design window size and shading devices, and consequently it has an impact on lighting and cooling energy savings. Nowadays a lot of studies are ongoing all over the world to better integrate daylight in building design; new concepts like the daylight autonomy [11,12], the useful daylight illuminance [13,14] and the continuous daylight autonomy [15], consider the effect of daylight dynamically. In the effort of integrating all these aspects, a new global approach has to be encouraged for building design, which should include both thermal and visual comfort. Such a new approach becomes fundamental when windows are concerned, as they play a major role as a vehicle for solar gains and daylight. This role is even more important in summer when the control of solar radiation, combined with adequate room ventilation at night, can significantly reduce or avoid air conditioning demand and improve indoor environmental quality.
403
In the present work new indicators based on a statistical approach for visual and thermal comfort in free running buildings are introduced and some general conclusions following a global approach will be given. Such indicators are built starting from the most important physical parameters for thermal and visual comfort, namely the operative temperature and the illuminance. Their utility is finally tested on a simple test case concerning the correct dimensioning of a window and the choice of its optical properties.
2. Indicators for thermal comfort 2.1. Frequency of the operative temperature (FOT) It is the percentage of time within a given period during which a certain value of the operative temperature is achieved. It allows to easily identify the most frequent operative temperatures for a given building configuration and to compare them with those obtained with other building solutions (e.g. by modifying insulation, shadings, glazing, etc.) in order to evaluate the effectiveness of each design variation with respect to a reference solution. The analysis on a daily basis is strictly recommended especially for evaluating the performance of movable shading devices; for more general purposes, even the monthly frequency of the operative temperatures might be used. In the case of buildings that are not used all day long (offices, schools, etc.), this percentage should be calculated over the actual time of occupancy, then excluding from the statistical analysis the values measured out of the occupancy time, as they are not significant for the evaluation of the thermal comfort. This indicator is not useful for choosing regulation strategies (neither for ventilation nor for thermal issues), since it does not provide any information concerning the actual time when a certain value of operative temperature occurs. 2.2. Frequency of thermal comfort conditions (FTC) It is the percentage of time within a given period during which the indoor thermal comfort conditions are accomplished; to this aim three ranges can be defined, delimited by two temperatures (Tover , Tunder ): • if Top < Tunder the occupants might suffer from cold sensation; • if Tunder ≤ Top ≤ Tover the thermal comfort is accomplished; • if Top > Tover the occupants might suffer from hot sensation. The definition of such ranges should comply with the adaptive thermal comfort criterion introduced in [7] and based on the calculation of the comfort operative temperature as a function of the running mean outdoor temperature. The running mean temperature is defined by referring to the previous few days, and by giving a different weight to each day, as shown by Eq. (1); Nicol and Humphreys found out that ˛ = 0.8 should be used [5]. More details about the application of Eq. (1) are reported in [16]. Tmr () = (1 − ˛) ·
n
Tout ( − j) · ˛j−1
(1)
j=1
In [7] three categories of comfort are introduced. Category I holds over a range of four degrees, and corresponds to a high level of expectation; its lower and upper limits are defined according to Eq. (2). Category II corresponds to a normal level of expectation, and is recommended for the design of new buildings while Category III corresponds to a moderate level of expectation and should be
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F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410 Category I Category III
32
Category II Outdoor running mean temp
30
Temperature [°C]
28 26 24 22 20 18 16 14 1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
Days of the month Fig. 1. Identification of the adaptive comfort categories for Lyon (August).
Fig. 3. Examples of overheating with the same ITD and different FD.
used for existing buildings. Out of these three categories, thermal comfort is not fulfilled (Category IV).
performed according to Eqs. (3) and (4) (see also Fig. 2):
Tunder,cat I = 16.8 + 0.33 · Trm
ITDover =
Tover,cat I = 20.8 + 0.33 · Trm (2)
In this study the limit values of Category I are used to define Tunder and Tover , as the authors reckon that a too large range of acceptability might make the indicators defined in the following less effective. According to the same concept, one can also calculate the frequency of thermal discomfort (FTD) for heat and cold, as the percentage of time during which Category I is not accomplished; in this case, as already introduced by the EN Standard 15251, it is also possible to indicate the occurrence of each category out of Category I. It is important to underline that the definition of the categories depends on the outdoor temperature; therefore the ranges of comfort for each category vary every day and for any site. For instance, the operative temperature limits for categories I, II and III for Lyon (France, Lat. 45◦ 45 N, Long. 4◦ 32 E) in August are shown in Fig. 1. In this case, Category I is accomplished for the greatest part of the month by means of operative temperatures between 24 and 28 ◦ C. The FTC indicator is useful to compare the effectiveness of different technical solutions and systems for improving the thermal comfort in free running buildings, on a short time basis or on a seasonal perspective. 2.3. Intensity of thermal discomfort (ITD) It is defined as the time integral of the difference between the current operative temperature and the upper limit of comfort (Tover ) or the lower limit of comfort (Tunder ); its calculation is then
Tover () · d
where Tover ()
P
=
Top () − Tover 0
if Top () ≥ Tover if Top () < Tover
(3)
ITDunder =
Tunder () · d
where
P
Tunder () =
Tunder − Top () 0
if Top () ≤ Tunder if Top () > Tunder
(4)
Here, P is the period over which the integration is performed; one can choose P = 1 day or P = 1 month. As shown in the previous sub-section, the values of Tover and Tunder must be updated at each day of the analysis, according to the adaptive comfort theory. The definition of the ITD is similar to that of integrated discomfort degree introduced by Zhang et al. [17]; however, their parameter is built by using the indoor air temperature and constant lower and upper limits, so neglecting the adaptive concept and the importance of the operative temperature for assessing thermal comfort. As the ITD gets higher, the discomfort for overheating or overcooling is more important; furthermore, a same value of the ITD obtained by means of two different building solutions means that they allow the achievement of the same average thermal comfort over the period of integration. When working on buildings that are occupied only during certain periods of time (offices, schools), the integration should be limited only to those periods. 2.4. Fluctuation of thermal discomfort (FD) As one can see in Fig. 3, different indoor operative temperature profiles might occur, characterized by the same ITD; three situations can be envisaged:
Fig. 2. Definition of intensity of thermal discomfort (ITD).
- Case A: the operative temperature is constantly higher than the upper limit, thus determining a stable and moderate sensation of discomfort; - Case B: the operative temperature fluctuates around the upper limit, which is exceeded during a considerable part of the day, thus producing a long-lasting and less moderate sensation of discomfort; - Case C: the operative temperature is normally lower than the upper limit, but a sharp variation occurs during a limited period of time, thus determining a brief but intense sensation of discomfort;
FTDover [%]
F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
Zone 2: Frequent but not intense discomfort
Zone 4: Frequent and intense discomfort
Zone 1: Light and temporary discomfort
Zone 3: Temporary but intense discomfort
daylight, such as to provide visual comfort conditions. To this aim, three ranges can be defined, delimited by two values of daylight illuminance (Eover , Eunder ): • if E < Eunder there is an insufficient daylighting and the occupants are obliged to use artificial lighting; • if Eunder ≤ E ≤ Eover the visual comfort is guaranteed thanks to daylight only; • if E > Eover there is an excessive daylighting and glare may occur.
ITDover [ºC.h/day] Fig. 4. Frequency of thermal discomfort (FTDover ) vs intensity of thermal discomfort (ITDover ).
In order to make a distinction among these different situations it is possible to introduce an indicator called fluctuation of thermal discomfort (FD), defined as the ratio of the intensity of thermal discomfort (ITDover ) to the length of the period when thermal discomfort is actually perceived, as reported in Eq. (5):
Tover () · d FDover =
P
=
ITDover
i+ · d
=
P
where i+
i+ · d P
1 if Top () ≥ Tover 0 if Top () < Tover
(5)
Of course, it results FDA < FDB < FDC . The calculation of this indicator might help to find out the best solution for improving thermal comfort. As an example, for a given high ITD value, a building characterized by a low FD is often in the discomfort region (case A), then an improvement of the thermal performance of the whole building might be required. On the contrary, a high value of FD means that discomfort occurs rarely but in an intense way (case C); in this case one might think to tackle the problem with a temporary more intense ventilation or a more efficient shading solution. The fluctuation of discomfort can also be regarded as the daily average number of degrees over the temperature limit that defines Category I. In order to facilitate the assessment of the thermal comfort of a building and to easily individuate the better way to improve it, some of the parameters previously introduced might be combined in diagrams such as the one shown in Fig. 4. As a general rule, four zones can be identified: -
405
Zone 1: light and temporary thermal discomfort; Zone 2: frequent but not intense thermal discomfort; Zone 3: temporary but intense thermal discomfort; Zone 4: frequent and intense thermal discomfort.
In the first and in the third situation one could also define the frequency of visual discomfort (FVD) for insufficient or excessive daylight illuminance, respectively. The concept behind the definition of the FVC is similar to the useful daylight illuminance introduced by Nabil and Mardaljevic [14]. The main difference is that UDI criterion is based on spatial rendering of useful daylight illuminance and it should be fulfilled in every point of the calculation grid. On the contrary, by using the FVC the authors propose here to work on an average daylight illuminance, since the aim is the definition of a simplified approach to integrate visual and thermal comfort in a simple but effective way. The definition of the range of visual comfort is critical, as it depends on the actual working context, the visual task, the luminance all around, etc. Many researches based on surveys set the upper limit at 2000 lux and the lower limit at 100 lux [13,14]. Following the approach of the authors based on the average daylight illuminance, the compliance of the same range is not suitable since it would not avoid too high or too low daylight illuminance locally. In the present work Eover = 750 lux and Eunder = 150 lux are assumed; nevertheless, these values can be varied depending on the design requirements, the actual use of the building and the visual task. The FVC indicator is useful to compare the global visual effectiveness of different technical solutions and systems (for daylight control and exploitation) on a monthly or annual basis. 3.2. Intensity of visual discomfort (IVD) It is defined as the time integral of the difference between the spatial average of the current daylight illuminance and the upper limit of visual comfort (Eover , here set at 750 lux) or the lower limit of visual comfort (Eunder , here set at 150 lux); its calculation is then performed according to Eqs. (6) and (7):
IVDover =
Eover () · d
=
3. Indicators for visual comfort from daylight 3.1. Frequency of visual comfort (FVC) It is the percentage of time within a certain period during which appropriate values of illuminance are accomplished thanks to
E() − Eover
if E() ≥ Eover
0
if E() < Eover
(6)
IVDunder =
Eunder () · d
where Eunder ()
P
=
This diagram can assist the definition of the strategies for improvement; as an example, it could provide information about the frequency and the intensity of the night ventilation which has to be introduced in order to improve thermal comfort.
where Eover ()
P
Eunder − E()
if E() ≤ Eunder
0
if E() > Eunder
(7)
As these indicators get higher, the visual discomfort for excessive or insufficient daylight is more important, respectively; actually, if IVDover > 0 one should talk about excessive daylight rather than visual discomfort, which is mostly related to glare. Coherently to their definition, the value of IVD is always greater than or equal to zero. Actually, it is very difficult to get IVD = 0 over a long period of time; however, even if IVD > 0 it does not necessarily mean that the situation is not acceptable. The authors believe that an acceptability threshold should be introduced: when the IVD is
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F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410 Size 30% - normal Size 20% - solar control
31
Size 20% - normal Size 20% - low emissivity
Size 10% - normal
Temperature [°C]
30 29 28 27 26 25
Upper limit of cate gory I
24 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
Time [h] Fig. 6. Operative (14/08–16/08).
temperature
Size 30% - normal Size 20% - solar control
profile
during
three
Size 20% - normal Size 20% - low emissivity
representative
days
Size 10% - normal
Indoor illuminance [lux]
3000 2500 2000 1500 1000 500 0 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
Time [h]
Fig. 5. Top: 3D model of the simulated test cell—the size of the window depends on the case study (see Table 1). Bottom: grid for the calculation of the illuminance. Table 1 Main inputs for the simulation of the test cell. Parameter
Value
Cell dimension Hygienic ventilation Night ventilation Walls U-value Roof U-value Window size (WWR:30%) (WWR:20%) (WWR:10%) Double glazing Time of occupancy Rate of occupancy People thermal load Appliances
4 × 4 × 2.7 0.5 4 0.45 0.4 2.5 × 1.3 1.8 × 1.2 0.9 × 1.2 4–12 (air) – 4 from 08:00 0.12 130 300
[m3 ] [ACH] [ACH] [W m−2 K−1 ] [W m−2 K−1 ] [m2 ] [m2 ] [m2 ] [mm] to 18:00 [people m−2 ] [W person−1 ] [W]
Table 2 Properties of the glazing considered in the simulations of step 2. Type of glass
Normal
Solar control
Low emissivity
Solar transmittance Visible transmittance Emissivity
0.78 0.88 0.84
0.48 0.57 0.84
0.68 0.81 0.2
lower than such a threshold, one can consider that visual discomfort is almost negligible. The authors propose to define the threshold according to the following criterion: the illuminance limits Eover and Eunder can be overcome at most for the 20% of time, and in any case for not more than the 30% of their value.
Fig. 7. Daylight average illuminance profile during three representative days (14/08–16/08).
A same value of these indicators obtained by means of two different building solutions means that they allow on average the achievement of the same degree of visual comfort over the period of integration. When working on buildings that are occupied only during certain periods of time (offices, schools), the integration should be limited only to those periods. 4. Coupling visual and thermal comfort It is not easy to introduce a single indicator which could evaluate at the same time both visual and indoor thermal comfort; actually, people might attach different importance to these two sides of a comfortable building, thus surveys should be performed in order to understand whether and to what extent an average occupant would accept, as an example, to withstand an uncomfortable temperature provided that the right illuminance is achieved. For this reason, the authors believe that the best way to have a more comprehensive look on the overall indoor comfort conditions might be just a critical synchronous analysis of some of the indicators previously introduced. The choice of the indicators to be compared has to be made with care and intelligence. As an example, when studying the performance of a free-running building with the aim of minimising its energy needs and, at the same time, optimizing its capacity to provide comfort to the occupants, one could meet the problem of choosing the right size and/or typology of glazing. As a matter of fact, the oversized window could enhance the deployment of daylight, but produce overheating, especially in warm and sunny climates; on the contrary, by reducing the window surface one could limit the solar radiation income, thus avoiding overheating but incurring in a too low daylight illuminance.
F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
Distribuon of the adapve categories (August) (a)
Window 20%
1600
Window 10%
1400
40%
Occurrence [%]
September
1800
FTC
ITD over [°C·h]
50%
(b)
2000
60%
Window 30%
407
30% 20%
1200
August
FDover
July June
2,4
1000 800 600
1,6 2,3
400
10%
200
1,5
0,7 1,0
Window 20%
Window 10%
0
0% IV cold III cold
II cold
Window 30%
I cat
II heat
Window 20%
Window 30%
III heat IV heat
Window 10%
(c)
100%
Daily FTD for heat [%]
90% 80%
August
70% 60% 50% 40% 30% 20% 10% 0% 0
5
10
15
20
25
30
Daily ITD over [°C·h]
Daylight illuminance distribuon (August) Window 30%
80%
Window 20%
FVC
1000
August July
Window 10%
IVD over [klux·h]
Occurrence [%]
September
90%
70%
(e)
1200
(d)
100%
60% 50% 40% 30% 20%
800
June
600 400 Acceptability Threshold
200
10%
0
0% < 150 lux
150 < E < 750 lux
> 750 lux
Window 30%
Window 20%
Window 10%
Fig. 8. Parameters for the statistical analysis of thermal and visual comfort—step 1.
To this aim it seems very interesting to compare the values of the intensity of thermal discomfort for overheating (ITDover ) and the intensity of visual discomfort for insufficient daylight illuminance (IVDunder ); furthermore one could compare the values of the frequency of thermal comfort (FTC) and the frequency of visual comfort (FVC). The evaluation of their values over a significant period of time – e.g. the whole summer season – would help the designer choose the best size, typology and shading device for a window in a free-running low-energy building. In the following, an example of the utility of such an approach is discussed. 5. Examples of application In order to show the usefulness of the statistical approach presented in this work, two examples of application will be provided,
that allow drawing interesting conclusions. To this aim, a simple 3D model of a test cell with a window on its south-oriented fac¸ade was considered; the model is represented in Fig. 5. The reflectivity of interior walls, ceiling and floor was set at 0.5, 0.7 and 0.3, respectively. The energy performance of the cell was simulated on EnergyPlus v6.0 [18] with the aim of calculating the daily profiles of operative temperature and daylight illuminance over the warm season (from June to September) by using the weather file of Lyon (France) available on the same software. The main inputs for the simulations are reported in Table 1. As far as the daylight illuminance is concerned, it was calculated on a grid of 16 points evenly distributed across the occupied area at a height of 0.8 m; the area close to the walls has been excluded from the illuminance calculation (see Fig. 5). The first series of simulations (step 1) aims at investigating the influence of the window size on thermal and visual comfort,
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F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
Distribuon of the adapve categories (August)
(a)
August
1600
Solar Control
ITD over [°C·h]
FTC
Low emissivity
Occurrence [%]
September
1800
Normal 50%
(b)
2000
60%
40% 30% 20%
July
1400
June
1200 1000
FDover
800 600
1,6
400
10%
200
1,5 1,2
1,5 1,2
1,4
0
0% IV cold III cold
Normal
II cold
I cat
II heat III heat IV heat
Solar Control
Low emissivity
Normal
Solar Control
Low emissivity
(c)
100%
Daily FTD for heat [%]
90% 80%
August
70% 60% 50% 40% 30% 20% 10% 0% 0
5
10
15
20
25
30
Daily ITD over [°C·h]
Daylight illuminance distribuon (August)
(d)
Normal
80%
Solar Co ntrol
1000
FVC
August July
Low emissivity
IVD over [klux·h]
Occurrence [%]
September
90%
70%
(e)
1200
100%
60% 50% 40% 30% 20%
800
June
600 400
Acceptability Threshold
200
10%
0
0% < 150 lux
150 < E < 750 lux
> 750 lux
Normal
Solar Control
Low emissivity
Fig. 9. Parameters for the statistical analysis of thermal and visual comfort—step 2.
assessed through the indicators previously introduced. Three cases were considered, with values of the ratio of window to wall area (WWR) as high as 10%, 20%, and 30%, respectively. Then, a second series of simulations was performed (step 2) with the aim of comparing the effect of different type of double glazing (with normal, solar control or LoE glasses), whose area was set at 20% of the fac¸ade. The main properties of each pane of the glazing proposed in this analysis are shown in Table 2. The solutions described above are also evaluated by crossing visual and thermal comfort indicators. 5.1. Step 1: the effect of the window size Figs. 6 and 7 illustrate the evolution of the operative temperature and the spatial average of the indoor daylight illuminance during three representative days in August for the three sizes of glazing surface proposed in step 1 as well as for three type of glazing
(step 2, see Section 5.2). The reduction of the window size produces a lower operative temperature (around 1 ◦ C for each step) and a lower daylight illuminance. The latter decreases almost proportionally to the size itself: as an example, on the second day a peak illuminance as high as 3000 lux is reached when adopting the largest window (30% of the fac¸ade), which reduces to 2000 lux and 1000 lux as a consequence of the choice of a smaller window (20% and 10%, respectively). However, the results displayed in these diagrams, despite clearly describing the effect of the window size, are limited to a very short period, and are not sufficient to perform an effective comparison over the whole warm season; to overcome these limitations, the indicators defined in the previous sections are calculated, and their values are reported in Fig. 8. The frequency of thermal comfort (FTC) is illustrated in Fig. 8a and shows the occurrence of the different comfort categories introduced by EN Standard 15251; in this study the thermal
F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
409
Fig. 10. Synchronous comparison of thermal and visual comfort.
comfort conditions correspond to category I. The diagrams refer to August; the occurrence is only evaluated during occupancy time (08:00–18:00). As one can easily understand, the smallest window seems to be the more appropriate solution, as it provides thermal comfort for around the 40% of the occupancy time (FTC = 0.39). The occurrence of very uncomfortable temperatures (category IV) is rare (around 2%), as opposed to the case of 30% glazed area, where a much more frequent intense thermal discomfort occurs (around 60% for category IV). Furthermore, as shown by Fig. 8b, the seasonal value of ITDover reduces from 1800 ◦ C h to just 300 ◦ C h; this means that, on a seasonal basis, the intensity of thermal discomfort is reduced by 85%. In the same diagram, the numbers included in the columns correspond, for the most uncomfortable months (July, August), to the value of the average FDover ; such information provides an estimation of the average amplitude of the hourly overheating perceived by the occupants. Fig. 8c informs about the daily occurrence of uncomfortable operative temperatures and the corresponding intensity of thermal discomfort in August; this diagram adds information to the previous ones as it provides a picture of the daily conditions. The best solution is the one for which the points converge toward the origin; however, it is possible to notice that even for a 10% glazed area, the occurrence of thermal discomfort is often higher than 50%. The reduction of the glazing surface has a major effect on the intensity of thermal discomfort, whereas its occurrence is still remarkable.
Concerning visual comfort, Fig. 8d suggests that a window as large as the 30% of the fac¸ade is oversized, as it produces excessive daylight illuminance for the 80% of the occupancy time; on the contrary, a 10% glazed area is more appropriate, as it induces visual comfort for the 70% of the occupancy time. The latter solution also generates insufficient daylight illuminance for the 7% of time; nevertheless, since the seasonal IVDunder (here not reported for brevity) is lower than the acceptability threshold defined in Section 3.2, it should not be a relevant problem. Finally, Fig. 8e shows that the intensity of visual discomfort for excessive daylight illuminance (IVDover ) could result much higher than the acceptability threshold if a proper size of the window is not chosen. A simultaneous analysis of thermal and visual comfort parameters is proposed in Fig. 10. Fig. 10a shows, for step 1, the comparison between the monthly values of the frequency of thermal comfort (FTC) and the frequency of visual comfort (FVC). The points associated with each solution are concentrated in well-separated areas on the diagram; it is interesting to underline that a given solution provides an almost constant value of the FVC during the warm season, whereas the FTC changes a lot throughout the different months. In any case, September is the month characterized by the most favourable thermal comfort and the worst visual comfort. Fig. 10b shows the comparison between the monthly values of the intensity of thermal discomfort for overheating (ITDover ) and the intensity of visual discomfort for insufficient daylight illuminance (IVDunder ). This diagram suggests that daylight illuminance
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F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
is rarely insufficient, whereas more problems occur as regards thermal comfort. One should prefer the solution characterized by a concentration of points closer to the origin. According to the analysis of all the diagrams, the more appropriate solution appears the one which adopts a glazing area as large as the 10% of the fac¸ade; however, even if visual comfort is fully satisfied, there still occurs a frequent but not intense thermal discomfort. Furthermore, the window may look too small if compared to the size of the test cell (only the 7% of the floor surface); hence, in the following the medium size window will be held, and other ways to further improve thermal and visual comfort will be investigated. 5.2. Step 2: the effect of the type of glazing As shown in Figs. 6 and 7, the use of a low-emissivity glazing does not produce visible changes if compared with a normal glass, both on the operative temperature and on the average daylight illuminance of the test cell. On the contrary, the adoption of a solar control glazing implies a lowering of the operative temperature in the test cell of about 0.5 ◦ C and a considerable reduction (about 40%) of the daylight illuminance. The statistical parameters reported in Fig. 9 help to perform such comparison on a seasonal basis. Thanks to the solar control glazing, it is possible to observe an increase in the FTC (Fig. 9a) as well as a decrease in the seasonal ITDover , which reduces of about 35% in comparison with the other solutions (Fig. 9b). The mean amplitude of the hourly overheating (FDover ) is also reduced of about 0.4 ◦ C in the hottest months; however, a frequent but not intense thermal discomfort still occurs (Fig. 9c). A considerable improvement of the visual comfort is also achieved, as witnessed by the increase in the FVC in August (Fig. 9d) and the substantial decrease of the IVDover , which is now only slightly higher than the acceptability threshold (Fig. 9e). According to Fig. 10c, the points related to the adoption of solar control glasses are concentrated in a well-separated area on the diagram. For a given month, a clear shift toward higher values of FVC and FTC can be identified if compared to the points associated with the other solutions; this shift is less appreciable during inter-seasonal periods (September). As in the previous analysis, for a given solution the FVC is relatively constant, whereas the FTC varies significantly; the normal and LoE glasses show similar behaviour during all the considered months. Furthermore, Fig. 10d suggests that the ITDover is still not sufficiently reduced. The installation of solar control glasses is then an effective solution for improving summer visual and thermal comfort in the test cell but is not sufficient to fulfil the hightest level of expectation for thermal comfort. With this aim other solutions should be provided (e.g. shading devices). 6. Conclusions In the present work an innovative statistical approach for the combined evaluation of thermal and visual comfort in buildings is presented; such an approach is based on the introduction of simple indicators that account for both the duration and the intensity of the potential discomfort. The statistical indicators can be used either separately or properly combined in order to obtain useful information about simultaneous effects of a building solution on thermal and visual comfort.
The proposed approach is mostly oriented at the analysis of free-running buildings, since it is inspired to existing dynamic approaches for daylight evaluation and to the concept of the adaptive comfort, codified by EN Standard 15251 and ASHRAE 55. It is therefore applicable as far as the restrictions stated in these standards are respected. After defining the parameters and the indicators necessary for the statistical evaluation, the application of the approach is shown through two examples concerning different design concepts, with the aim of understanding the effectiveness of each solution in comparison with the others. The use of the proposed indicators allows a wide and deep knowledge of thermal and visual comfort on a daily, monthly or seasonal basis, and it can orient the definition of optimum solutions. This simplified approach requires – as input data – only the hourly operative temperature and the hourly average daylight illuminance to manage a visual and thermal comfort analysis. It may have a large application since it can be used whenever an effective and quick comparison among several technical solutions has to be made; this can happen during the design phase for both new and existing buildings. Thanks to the wide range of application, the same approach is currently being adopted by the authors to evaluate the effectiveness of new materials (PCMs, VIP, etc.) and components (overhangs, venetian blinds, etc.) as well as for setting ventilation strategies; the results of such applications will be reported in following papers. References [1] P.O. Fanger, Thermal Comfort—Analysis and Applications in Environmental Engineering Copenhagen, Danish Technical Press, 1970. [2] SO Standard 7730, 1994, Moderate thermal environments—Determination of the PMV and PPD indices and specification of the conditions for thermal comfort, revised in 2005. [3] J.F. Nicol, M.A. Humphreys, Thermal comfort as part of a self-regulating system, in: Proceedings of the CIB Symposium on Thermal Comfort, Building research Establishment, Watford, UK, 1972. [4] R.J. de Dear, G.S. Brager, Thermal comfort in naturally ventilated buildings: revisions to ASHRAE Standard 55, Energy and Buildings 34 (2002) 549–561. [5] J.F. Nicol, M.A. Humphreys, Adaptive thermal comfort and sustainable thermal standards for buildings, Energy and Buildings 34 (2002) 563–572. [6] ASHRAE Standard 55, 2004, Thermal Environmental Condition for Human Occupancy, Atlanta, ASHRAE Inc. [7] EN Standard 15251, 2007, Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics. [8] N. Djongyang, R. Tchinda, D. Njomo, Thermal comfort: a review paper, Renewable and Sustainable Energy Reviews 14 (2010) 2626–2640. [9] EN Standard 12464-1, 2002, Light and lighting – lighting of work places - Part 1: indoor work places. [10] EN Standard 15193, 2007, Energy performance of Buildings—Energy requirements for lighting. [11] C.F. Reinhart, O. Walkenhorst, Dynamic radiance-based daylight simulations for a full-scale test office with outer venetian blinds, Energy and Buildings 33 (2001) 683–697. [12] C.F. Reinhart, J. Mardaljevic, Z. Roger, Dynamic daylight performance metrics for sustainable building design, Leukos 3 (July (1)) (2006) 1–25. [13] A. Nabil, J. Mardaljevic, Useful daylight illuminance: a new paradigm to access daylight in buildings, Light Research & Technology 37 (2005) 41–59. [14] A. Nabil, J. Mardaljevic, Useful daylight illuminances: a replacement for daylight factors, Energy and Buildings 38 (2006) 905–913. [15] Z. Roger, Daylight Metric Development Using Daylight Autonomy Calculations in the Sensor Placement Optimisation Tool, Boulder, Colorado, USA, 2006. [16] J.F. Nicol, M.A. Humphreys, Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN15251, Buildings and Environment 45 (2010) 11–17. [17] Y. Zhang, K. Lin, Q. Zhang, H. Di, Ideal thermophysical properties for free-cooling (or heating) buildings with constant thermal physical property material, Energy and Buildings 38 (2006) 1164–1170. [18] US Department of Energy, Energy Plus version 6.0, 2010, http://apps1.eere. energy.gov/buildings/energyplus.
Contents lists available at SciVerse ScienceDirect
Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
A statistical approach for the evaluation of thermal and visual comfort in free-running buildings Fabio Sicurella a,∗ , Gianpiero Evola a , Etienne Wurtz b a b
LEPMI – CNRS, 73376 Le Bourget-Du-Lac, France LEB – CEA – INES, 73376 Le Bourget-Du-Lac, France
a r t i c l e
i n f o
Article history: Received 19 March 2011 Received in revised form 22 September 2011 Accepted 12 December 2011 Keywords: Statistical indicators Thermal comfort Visual comfort Warm season Windows
a b s t r a c t In recent years, the study of indoor environmental comfort during the warm season has been one of the most attractive and hard tasks for architects and energy designers. Nowadays, thanks to the available high-performance utilities, the dynamic energy simulation of a building is relatively easy. Nevertheless, since it should simultaneously account for thermal, visual and air quality issues, a global approach, often neglected, becomes necessary. In the present work, an approach based on simple indicators calculated on a statistical basis will be presented; it can be useful for the simultaneous evaluation of the indoor thermal and visual comfort on a more comprehensive perspective, and it can be applied in any building energy analysis where a comparison between different solutions or strategies is required. At the end of the paper this approach is tested on a simple case study in order to show how the approach can be used to evaluate the influence of the size and the typology of a window on indoor comfort. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Almost thirty years ago the PMV-PPD model for thermal comfort proposed by Fanger [1] had a wide scientific consensus so that it was included, several years later, in the ISO Standard 7730 [2]. This approach, based on a steady-state energy balance on the human body, allows the prediction of thermal sensation and comfort satisfaction of the human body as a function of six parameters related to the indoor environment (internal temperature, air velocity, humidity, mean radiant temperature) and to the occupants (activity and clothing), without any correlation with the external environmental conditions. This model, developed by using the results of interviews carried out under controlled micro-climatic conditions (typical of buildings provided with HVAC systems), is not suitable to manage the transient state that occurs, for instance, in naturally ventilated buildings, in buildings without HVAC systems or where occupants vary their behaviour and activity. This means that for most bioclimatic buildings as well as for a large number of renewed buildings Fanger’s approach might not be suitable. On the other hand, in the same years the adaptive model proposed by Nicol and Humphreys [3] stated that people’s interaction with the external and internal environment allows a range of
∗ Corresponding author. E-mail addresses: [email protected], [email protected] (F. Sicurella), [email protected] (G. Evola), [email protected] (E. Wurtz). 0378-7788/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2011.12.013
thermal comfort conditions which is wider than that admitted by a steady-state model. Actually, people can react to changes in the environment by taking appropriate actions or by changing their attitudes, in order to restore a comfortable condition even if the environment where they are placed has undergone appreciable changes. de Dear and Brager [4] also underlined that people who live or work in naturally ventilated buildings, where they are able to open windows, get used to thermal variations reflecting local climatic patterns. By analysing a great number of surveys conducted world-wide on free-running buildings, Nicol and Humphreys [5] found a clear correlation between the comfort operative temperature and the running mean outdoor temperature measured over the previous days. As a consequence, they stated that thermal comfort in free-running buildings can be assessed just as a function of the indoor operative temperature, so neglecting all the other parameters accounted for in Fanger’s model, which would have a minor importance. Then, while Fanger’s approach intrinsically postulates the need of a system to provide and keep optimal thermal conditions inside the building, the adaptive approach just defines a range of temperatures in which an occupant can find his own comfort without the aid of any air-conditioning system, provided that he is free of adapting his behaviour and of operating on the openings to deploy natural ventilation. When studying low energy demand buildings, the adaptive approach appears much more appropriate, since no HVAC is postulated and a link is created between human behaviour, its interaction
F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
Nomenclature E Eover Eunder FOT FTC FTD FD FVC ITD IVD Tover Tunder Top Tout Trm
illuminance (lux) upper limit of the visual comfort range (lux) lower limit of the visual comfort range (lux) frequency of the operative temperature (%) frequency of thermal comfort conditions (%) frequency of thermal discomfort conditions (%) fluctuation of thermal discomfort (◦ C) frequency of visual comfort conditions (%) intensity of thermal discomfort (◦ C h) intensity of visual discomfort (lux h) upper limit of the thermal comfort range (◦ C) lower limit of the thermal comfort range (◦ C) operative temperature (◦ C) outdoor air temperature (◦ C) running mean outdoor temperature (◦ C) time (h)
with the environment and, as a consequence, the building energy demand. The importance of this approach has increased in the last ten years so that it was first included in the ASHRAE standard 55 [6] and more recently in the EN standard 15251 [7]. The latter provides, among other things, the acceptable indoor temperature ranges for buildings without mechanical ventilation systems. A comprehensive review of the approaches available to study thermal comfort is reported in [8]. Another fundamental aspect of the environmental comfort is the correct use of daylight. The definition and the quantification of visual comfort are less standardised than thermal comfort, since it depends on the available external daylight, on the glazing and screens that “filter” it, on the indoor environment (optical characteristic of walls) and, of course, on the visual task. The EN Standard 12464-1 [9] establishes the fundamental rules for artificial lighting in indoor work places and tackles the glare issues. But, up to now, no rules and suggestions have been given concerning the optimal values of daylight illuminance, its uniformity and glare; just a qualitative approach encouraging the integration between natural and artificial lighting is reported. The recent EN Standard 15193 [10] introduces a new indicator to evaluate energy consumption for lighting, which also includes the contribution of daylight. This approach is quite innovative since it allows the evaluation of lighting control logics based on the integration with the daylight for energy savings. Nevertheless, the daylight availability is still assessed through the calculation of the daylight factor, hence with a static approach, and cannot account neither for the real potential of natural lighting nor for the efficacy of dynamic shading devices. This lack is misleading, since a precise evaluation of the daylight availability is fundamental to correctly design window size and shading devices, and consequently it has an impact on lighting and cooling energy savings. Nowadays a lot of studies are ongoing all over the world to better integrate daylight in building design; new concepts like the daylight autonomy [11,12], the useful daylight illuminance [13,14] and the continuous daylight autonomy [15], consider the effect of daylight dynamically. In the effort of integrating all these aspects, a new global approach has to be encouraged for building design, which should include both thermal and visual comfort. Such a new approach becomes fundamental when windows are concerned, as they play a major role as a vehicle for solar gains and daylight. This role is even more important in summer when the control of solar radiation, combined with adequate room ventilation at night, can significantly reduce or avoid air conditioning demand and improve indoor environmental quality.
403
In the present work new indicators based on a statistical approach for visual and thermal comfort in free running buildings are introduced and some general conclusions following a global approach will be given. Such indicators are built starting from the most important physical parameters for thermal and visual comfort, namely the operative temperature and the illuminance. Their utility is finally tested on a simple test case concerning the correct dimensioning of a window and the choice of its optical properties.
2. Indicators for thermal comfort 2.1. Frequency of the operative temperature (FOT) It is the percentage of time within a given period during which a certain value of the operative temperature is achieved. It allows to easily identify the most frequent operative temperatures for a given building configuration and to compare them with those obtained with other building solutions (e.g. by modifying insulation, shadings, glazing, etc.) in order to evaluate the effectiveness of each design variation with respect to a reference solution. The analysis on a daily basis is strictly recommended especially for evaluating the performance of movable shading devices; for more general purposes, even the monthly frequency of the operative temperatures might be used. In the case of buildings that are not used all day long (offices, schools, etc.), this percentage should be calculated over the actual time of occupancy, then excluding from the statistical analysis the values measured out of the occupancy time, as they are not significant for the evaluation of the thermal comfort. This indicator is not useful for choosing regulation strategies (neither for ventilation nor for thermal issues), since it does not provide any information concerning the actual time when a certain value of operative temperature occurs. 2.2. Frequency of thermal comfort conditions (FTC) It is the percentage of time within a given period during which the indoor thermal comfort conditions are accomplished; to this aim three ranges can be defined, delimited by two temperatures (Tover , Tunder ): • if Top < Tunder the occupants might suffer from cold sensation; • if Tunder ≤ Top ≤ Tover the thermal comfort is accomplished; • if Top > Tover the occupants might suffer from hot sensation. The definition of such ranges should comply with the adaptive thermal comfort criterion introduced in [7] and based on the calculation of the comfort operative temperature as a function of the running mean outdoor temperature. The running mean temperature is defined by referring to the previous few days, and by giving a different weight to each day, as shown by Eq. (1); Nicol and Humphreys found out that ˛ = 0.8 should be used [5]. More details about the application of Eq. (1) are reported in [16]. Tmr () = (1 − ˛) ·
n
Tout ( − j) · ˛j−1
(1)
j=1
In [7] three categories of comfort are introduced. Category I holds over a range of four degrees, and corresponds to a high level of expectation; its lower and upper limits are defined according to Eq. (2). Category II corresponds to a normal level of expectation, and is recommended for the design of new buildings while Category III corresponds to a moderate level of expectation and should be
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F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410 Category I Category III
32
Category II Outdoor running mean temp
30
Temperature [°C]
28 26 24 22 20 18 16 14 1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
Days of the month Fig. 1. Identification of the adaptive comfort categories for Lyon (August).
Fig. 3. Examples of overheating with the same ITD and different FD.
used for existing buildings. Out of these three categories, thermal comfort is not fulfilled (Category IV).
performed according to Eqs. (3) and (4) (see also Fig. 2):
Tunder,cat I = 16.8 + 0.33 · Trm
ITDover =
Tover,cat I = 20.8 + 0.33 · Trm (2)
In this study the limit values of Category I are used to define Tunder and Tover , as the authors reckon that a too large range of acceptability might make the indicators defined in the following less effective. According to the same concept, one can also calculate the frequency of thermal discomfort (FTD) for heat and cold, as the percentage of time during which Category I is not accomplished; in this case, as already introduced by the EN Standard 15251, it is also possible to indicate the occurrence of each category out of Category I. It is important to underline that the definition of the categories depends on the outdoor temperature; therefore the ranges of comfort for each category vary every day and for any site. For instance, the operative temperature limits for categories I, II and III for Lyon (France, Lat. 45◦ 45 N, Long. 4◦ 32 E) in August are shown in Fig. 1. In this case, Category I is accomplished for the greatest part of the month by means of operative temperatures between 24 and 28 ◦ C. The FTC indicator is useful to compare the effectiveness of different technical solutions and systems for improving the thermal comfort in free running buildings, on a short time basis or on a seasonal perspective. 2.3. Intensity of thermal discomfort (ITD) It is defined as the time integral of the difference between the current operative temperature and the upper limit of comfort (Tover ) or the lower limit of comfort (Tunder ); its calculation is then
Tover () · d
where Tover ()
P
=
Top () − Tover 0
if Top () ≥ Tover if Top () < Tover
(3)
ITDunder =
Tunder () · d
where
P
Tunder () =
Tunder − Top () 0
if Top () ≤ Tunder if Top () > Tunder
(4)
Here, P is the period over which the integration is performed; one can choose P = 1 day or P = 1 month. As shown in the previous sub-section, the values of Tover and Tunder must be updated at each day of the analysis, according to the adaptive comfort theory. The definition of the ITD is similar to that of integrated discomfort degree introduced by Zhang et al. [17]; however, their parameter is built by using the indoor air temperature and constant lower and upper limits, so neglecting the adaptive concept and the importance of the operative temperature for assessing thermal comfort. As the ITD gets higher, the discomfort for overheating or overcooling is more important; furthermore, a same value of the ITD obtained by means of two different building solutions means that they allow the achievement of the same average thermal comfort over the period of integration. When working on buildings that are occupied only during certain periods of time (offices, schools), the integration should be limited only to those periods. 2.4. Fluctuation of thermal discomfort (FD) As one can see in Fig. 3, different indoor operative temperature profiles might occur, characterized by the same ITD; three situations can be envisaged:
Fig. 2. Definition of intensity of thermal discomfort (ITD).
- Case A: the operative temperature is constantly higher than the upper limit, thus determining a stable and moderate sensation of discomfort; - Case B: the operative temperature fluctuates around the upper limit, which is exceeded during a considerable part of the day, thus producing a long-lasting and less moderate sensation of discomfort; - Case C: the operative temperature is normally lower than the upper limit, but a sharp variation occurs during a limited period of time, thus determining a brief but intense sensation of discomfort;
FTDover [%]
F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
Zone 2: Frequent but not intense discomfort
Zone 4: Frequent and intense discomfort
Zone 1: Light and temporary discomfort
Zone 3: Temporary but intense discomfort
daylight, such as to provide visual comfort conditions. To this aim, three ranges can be defined, delimited by two values of daylight illuminance (Eover , Eunder ): • if E < Eunder there is an insufficient daylighting and the occupants are obliged to use artificial lighting; • if Eunder ≤ E ≤ Eover the visual comfort is guaranteed thanks to daylight only; • if E > Eover there is an excessive daylighting and glare may occur.
ITDover [ºC.h/day] Fig. 4. Frequency of thermal discomfort (FTDover ) vs intensity of thermal discomfort (ITDover ).
In order to make a distinction among these different situations it is possible to introduce an indicator called fluctuation of thermal discomfort (FD), defined as the ratio of the intensity of thermal discomfort (ITDover ) to the length of the period when thermal discomfort is actually perceived, as reported in Eq. (5):
Tover () · d FDover =
P
=
ITDover
i+ · d
=
P
where i+
i+ · d P
1 if Top () ≥ Tover 0 if Top () < Tover
(5)
Of course, it results FDA < FDB < FDC . The calculation of this indicator might help to find out the best solution for improving thermal comfort. As an example, for a given high ITD value, a building characterized by a low FD is often in the discomfort region (case A), then an improvement of the thermal performance of the whole building might be required. On the contrary, a high value of FD means that discomfort occurs rarely but in an intense way (case C); in this case one might think to tackle the problem with a temporary more intense ventilation or a more efficient shading solution. The fluctuation of discomfort can also be regarded as the daily average number of degrees over the temperature limit that defines Category I. In order to facilitate the assessment of the thermal comfort of a building and to easily individuate the better way to improve it, some of the parameters previously introduced might be combined in diagrams such as the one shown in Fig. 4. As a general rule, four zones can be identified: -
405
Zone 1: light and temporary thermal discomfort; Zone 2: frequent but not intense thermal discomfort; Zone 3: temporary but intense thermal discomfort; Zone 4: frequent and intense thermal discomfort.
In the first and in the third situation one could also define the frequency of visual discomfort (FVD) for insufficient or excessive daylight illuminance, respectively. The concept behind the definition of the FVC is similar to the useful daylight illuminance introduced by Nabil and Mardaljevic [14]. The main difference is that UDI criterion is based on spatial rendering of useful daylight illuminance and it should be fulfilled in every point of the calculation grid. On the contrary, by using the FVC the authors propose here to work on an average daylight illuminance, since the aim is the definition of a simplified approach to integrate visual and thermal comfort in a simple but effective way. The definition of the range of visual comfort is critical, as it depends on the actual working context, the visual task, the luminance all around, etc. Many researches based on surveys set the upper limit at 2000 lux and the lower limit at 100 lux [13,14]. Following the approach of the authors based on the average daylight illuminance, the compliance of the same range is not suitable since it would not avoid too high or too low daylight illuminance locally. In the present work Eover = 750 lux and Eunder = 150 lux are assumed; nevertheless, these values can be varied depending on the design requirements, the actual use of the building and the visual task. The FVC indicator is useful to compare the global visual effectiveness of different technical solutions and systems (for daylight control and exploitation) on a monthly or annual basis. 3.2. Intensity of visual discomfort (IVD) It is defined as the time integral of the difference between the spatial average of the current daylight illuminance and the upper limit of visual comfort (Eover , here set at 750 lux) or the lower limit of visual comfort (Eunder , here set at 150 lux); its calculation is then performed according to Eqs. (6) and (7):
IVDover =
Eover () · d
=
3. Indicators for visual comfort from daylight 3.1. Frequency of visual comfort (FVC) It is the percentage of time within a certain period during which appropriate values of illuminance are accomplished thanks to
E() − Eover
if E() ≥ Eover
0
if E() < Eover
(6)
IVDunder =
Eunder () · d
where Eunder ()
P
=
This diagram can assist the definition of the strategies for improvement; as an example, it could provide information about the frequency and the intensity of the night ventilation which has to be introduced in order to improve thermal comfort.
where Eover ()
P
Eunder − E()
if E() ≤ Eunder
0
if E() > Eunder
(7)
As these indicators get higher, the visual discomfort for excessive or insufficient daylight is more important, respectively; actually, if IVDover > 0 one should talk about excessive daylight rather than visual discomfort, which is mostly related to glare. Coherently to their definition, the value of IVD is always greater than or equal to zero. Actually, it is very difficult to get IVD = 0 over a long period of time; however, even if IVD > 0 it does not necessarily mean that the situation is not acceptable. The authors believe that an acceptability threshold should be introduced: when the IVD is
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F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410 Size 30% - normal Size 20% - solar control
31
Size 20% - normal Size 20% - low emissivity
Size 10% - normal
Temperature [°C]
30 29 28 27 26 25
Upper limit of cate gory I
24 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
Time [h] Fig. 6. Operative (14/08–16/08).
temperature
Size 30% - normal Size 20% - solar control
profile
during
three
Size 20% - normal Size 20% - low emissivity
representative
days
Size 10% - normal
Indoor illuminance [lux]
3000 2500 2000 1500 1000 500 0 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
6.00 12.00 18.00 0.00
Time [h]
Fig. 5. Top: 3D model of the simulated test cell—the size of the window depends on the case study (see Table 1). Bottom: grid for the calculation of the illuminance. Table 1 Main inputs for the simulation of the test cell. Parameter
Value
Cell dimension Hygienic ventilation Night ventilation Walls U-value Roof U-value Window size (WWR:30%) (WWR:20%) (WWR:10%) Double glazing Time of occupancy Rate of occupancy People thermal load Appliances
4 × 4 × 2.7 0.5 4 0.45 0.4 2.5 × 1.3 1.8 × 1.2 0.9 × 1.2 4–12 (air) – 4 from 08:00 0.12 130 300
[m3 ] [ACH] [ACH] [W m−2 K−1 ] [W m−2 K−1 ] [m2 ] [m2 ] [m2 ] [mm] to 18:00 [people m−2 ] [W person−1 ] [W]
Table 2 Properties of the glazing considered in the simulations of step 2. Type of glass
Normal
Solar control
Low emissivity
Solar transmittance Visible transmittance Emissivity
0.78 0.88 0.84
0.48 0.57 0.84
0.68 0.81 0.2
lower than such a threshold, one can consider that visual discomfort is almost negligible. The authors propose to define the threshold according to the following criterion: the illuminance limits Eover and Eunder can be overcome at most for the 20% of time, and in any case for not more than the 30% of their value.
Fig. 7. Daylight average illuminance profile during three representative days (14/08–16/08).
A same value of these indicators obtained by means of two different building solutions means that they allow on average the achievement of the same degree of visual comfort over the period of integration. When working on buildings that are occupied only during certain periods of time (offices, schools), the integration should be limited only to those periods. 4. Coupling visual and thermal comfort It is not easy to introduce a single indicator which could evaluate at the same time both visual and indoor thermal comfort; actually, people might attach different importance to these two sides of a comfortable building, thus surveys should be performed in order to understand whether and to what extent an average occupant would accept, as an example, to withstand an uncomfortable temperature provided that the right illuminance is achieved. For this reason, the authors believe that the best way to have a more comprehensive look on the overall indoor comfort conditions might be just a critical synchronous analysis of some of the indicators previously introduced. The choice of the indicators to be compared has to be made with care and intelligence. As an example, when studying the performance of a free-running building with the aim of minimising its energy needs and, at the same time, optimizing its capacity to provide comfort to the occupants, one could meet the problem of choosing the right size and/or typology of glazing. As a matter of fact, the oversized window could enhance the deployment of daylight, but produce overheating, especially in warm and sunny climates; on the contrary, by reducing the window surface one could limit the solar radiation income, thus avoiding overheating but incurring in a too low daylight illuminance.
F. Sicurella et al. / Energy and Buildings 47 (2012) 402–410
Distribuon of the adapve categories (August) (a)
Window 20%
1600
Window 10%
1400
40%
Occurrence [%]
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50%
(b)
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1,6 2,3
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0% IV cold III cold
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III heat IV heat
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(c)
100%
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August
70% 60% 50% 40% 30% 20% 10% 0% 0
5
10
15
20
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30
Daily ITD over [°C·h]
Daylight illuminance distribuon (August) Window 30%
80%
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FVC
1000
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Occurrence [%]
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(d)
100%
60% 50% 40% 30% 20%
800
June
600 400 Acceptability Threshold
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10%
0
0% < 150 lux
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> 750 lux
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Window 20%
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Fig. 8. Parameters for the statistical analysis of thermal and visual comfort—step 1.
To this aim it seems very interesting to compare the values of the intensity of thermal discomfort for overheating (ITDover ) and the intensity of visual discomfort for insufficient daylight illuminance (IVDunder ); furthermore one could compare the values of the frequency of thermal comfort (FTC) and the frequency of visual comfort (FVC). The evaluation of their values over a significant period of time – e.g. the whole summer season – would help the designer choose the best size, typology and shading device for a window in a free-running low-energy building. In the following, an example of the utility of such an approach is discussed. 5. Examples of application In order to show the usefulness of the statistical approach presented in this work, two examples of application will be provided,
that allow drawing interesting conclusions. To this aim, a simple 3D model of a test cell with a window on its south-oriented fac¸ade was considered; the model is represented in Fig. 5. The reflectivity of interior walls, ceiling and floor was set at 0.5, 0.7 and 0.3, respectively. The energy performance of the cell was simulated on EnergyPlus v6.0 [18] with the aim of calculating the daily profiles of operative temperature and daylight illuminance over the warm season (from June to September) by using the weather file of Lyon (France) available on the same software. The main inputs for the simulations are reported in Table 1. As far as the daylight illuminance is concerned, it was calculated on a grid of 16 points evenly distributed across the occupied area at a height of 0.8 m; the area close to the walls has been excluded from the illuminance calculation (see Fig. 5). The first series of simulations (step 1) aims at investigating the influence of the window size on thermal and visual comfort,
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Distribuon of the adapve categories (August)
(a)
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Solar Control
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August
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Daylight illuminance distribuon (August)
(d)
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FVC
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Low emissivity
IVD over [klux·h]
Occurrence [%]
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90%
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(e)
1200
100%
60% 50% 40% 30% 20%
800
June
600 400
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200
10%
0
0% < 150 lux
150 < E < 750 lux
> 750 lux
Normal
Solar Control
Low emissivity
Fig. 9. Parameters for the statistical analysis of thermal and visual comfort—step 2.
assessed through the indicators previously introduced. Three cases were considered, with values of the ratio of window to wall area (WWR) as high as 10%, 20%, and 30%, respectively. Then, a second series of simulations was performed (step 2) with the aim of comparing the effect of different type of double glazing (with normal, solar control or LoE glasses), whose area was set at 20% of the fac¸ade. The main properties of each pane of the glazing proposed in this analysis are shown in Table 2. The solutions described above are also evaluated by crossing visual and thermal comfort indicators. 5.1. Step 1: the effect of the window size Figs. 6 and 7 illustrate the evolution of the operative temperature and the spatial average of the indoor daylight illuminance during three representative days in August for the three sizes of glazing surface proposed in step 1 as well as for three type of glazing
(step 2, see Section 5.2). The reduction of the window size produces a lower operative temperature (around 1 ◦ C for each step) and a lower daylight illuminance. The latter decreases almost proportionally to the size itself: as an example, on the second day a peak illuminance as high as 3000 lux is reached when adopting the largest window (30% of the fac¸ade), which reduces to 2000 lux and 1000 lux as a consequence of the choice of a smaller window (20% and 10%, respectively). However, the results displayed in these diagrams, despite clearly describing the effect of the window size, are limited to a very short period, and are not sufficient to perform an effective comparison over the whole warm season; to overcome these limitations, the indicators defined in the previous sections are calculated, and their values are reported in Fig. 8. The frequency of thermal comfort (FTC) is illustrated in Fig. 8a and shows the occurrence of the different comfort categories introduced by EN Standard 15251; in this study the thermal
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Fig. 10. Synchronous comparison of thermal and visual comfort.
comfort conditions correspond to category I. The diagrams refer to August; the occurrence is only evaluated during occupancy time (08:00–18:00). As one can easily understand, the smallest window seems to be the more appropriate solution, as it provides thermal comfort for around the 40% of the occupancy time (FTC = 0.39). The occurrence of very uncomfortable temperatures (category IV) is rare (around 2%), as opposed to the case of 30% glazed area, where a much more frequent intense thermal discomfort occurs (around 60% for category IV). Furthermore, as shown by Fig. 8b, the seasonal value of ITDover reduces from 1800 ◦ C h to just 300 ◦ C h; this means that, on a seasonal basis, the intensity of thermal discomfort is reduced by 85%. In the same diagram, the numbers included in the columns correspond, for the most uncomfortable months (July, August), to the value of the average FDover ; such information provides an estimation of the average amplitude of the hourly overheating perceived by the occupants. Fig. 8c informs about the daily occurrence of uncomfortable operative temperatures and the corresponding intensity of thermal discomfort in August; this diagram adds information to the previous ones as it provides a picture of the daily conditions. The best solution is the one for which the points converge toward the origin; however, it is possible to notice that even for a 10% glazed area, the occurrence of thermal discomfort is often higher than 50%. The reduction of the glazing surface has a major effect on the intensity of thermal discomfort, whereas its occurrence is still remarkable.
Concerning visual comfort, Fig. 8d suggests that a window as large as the 30% of the fac¸ade is oversized, as it produces excessive daylight illuminance for the 80% of the occupancy time; on the contrary, a 10% glazed area is more appropriate, as it induces visual comfort for the 70% of the occupancy time. The latter solution also generates insufficient daylight illuminance for the 7% of time; nevertheless, since the seasonal IVDunder (here not reported for brevity) is lower than the acceptability threshold defined in Section 3.2, it should not be a relevant problem. Finally, Fig. 8e shows that the intensity of visual discomfort for excessive daylight illuminance (IVDover ) could result much higher than the acceptability threshold if a proper size of the window is not chosen. A simultaneous analysis of thermal and visual comfort parameters is proposed in Fig. 10. Fig. 10a shows, for step 1, the comparison between the monthly values of the frequency of thermal comfort (FTC) and the frequency of visual comfort (FVC). The points associated with each solution are concentrated in well-separated areas on the diagram; it is interesting to underline that a given solution provides an almost constant value of the FVC during the warm season, whereas the FTC changes a lot throughout the different months. In any case, September is the month characterized by the most favourable thermal comfort and the worst visual comfort. Fig. 10b shows the comparison between the monthly values of the intensity of thermal discomfort for overheating (ITDover ) and the intensity of visual discomfort for insufficient daylight illuminance (IVDunder ). This diagram suggests that daylight illuminance
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is rarely insufficient, whereas more problems occur as regards thermal comfort. One should prefer the solution characterized by a concentration of points closer to the origin. According to the analysis of all the diagrams, the more appropriate solution appears the one which adopts a glazing area as large as the 10% of the fac¸ade; however, even if visual comfort is fully satisfied, there still occurs a frequent but not intense thermal discomfort. Furthermore, the window may look too small if compared to the size of the test cell (only the 7% of the floor surface); hence, in the following the medium size window will be held, and other ways to further improve thermal and visual comfort will be investigated. 5.2. Step 2: the effect of the type of glazing As shown in Figs. 6 and 7, the use of a low-emissivity glazing does not produce visible changes if compared with a normal glass, both on the operative temperature and on the average daylight illuminance of the test cell. On the contrary, the adoption of a solar control glazing implies a lowering of the operative temperature in the test cell of about 0.5 ◦ C and a considerable reduction (about 40%) of the daylight illuminance. The statistical parameters reported in Fig. 9 help to perform such comparison on a seasonal basis. Thanks to the solar control glazing, it is possible to observe an increase in the FTC (Fig. 9a) as well as a decrease in the seasonal ITDover , which reduces of about 35% in comparison with the other solutions (Fig. 9b). The mean amplitude of the hourly overheating (FDover ) is also reduced of about 0.4 ◦ C in the hottest months; however, a frequent but not intense thermal discomfort still occurs (Fig. 9c). A considerable improvement of the visual comfort is also achieved, as witnessed by the increase in the FVC in August (Fig. 9d) and the substantial decrease of the IVDover , which is now only slightly higher than the acceptability threshold (Fig. 9e). According to Fig. 10c, the points related to the adoption of solar control glasses are concentrated in a well-separated area on the diagram. For a given month, a clear shift toward higher values of FVC and FTC can be identified if compared to the points associated with the other solutions; this shift is less appreciable during inter-seasonal periods (September). As in the previous analysis, for a given solution the FVC is relatively constant, whereas the FTC varies significantly; the normal and LoE glasses show similar behaviour during all the considered months. Furthermore, Fig. 10d suggests that the ITDover is still not sufficiently reduced. The installation of solar control glasses is then an effective solution for improving summer visual and thermal comfort in the test cell but is not sufficient to fulfil the hightest level of expectation for thermal comfort. With this aim other solutions should be provided (e.g. shading devices). 6. Conclusions In the present work an innovative statistical approach for the combined evaluation of thermal and visual comfort in buildings is presented; such an approach is based on the introduction of simple indicators that account for both the duration and the intensity of the potential discomfort. The statistical indicators can be used either separately or properly combined in order to obtain useful information about simultaneous effects of a building solution on thermal and visual comfort.
The proposed approach is mostly oriented at the analysis of free-running buildings, since it is inspired to existing dynamic approaches for daylight evaluation and to the concept of the adaptive comfort, codified by EN Standard 15251 and ASHRAE 55. It is therefore applicable as far as the restrictions stated in these standards are respected. After defining the parameters and the indicators necessary for the statistical evaluation, the application of the approach is shown through two examples concerning different design concepts, with the aim of understanding the effectiveness of each solution in comparison with the others. The use of the proposed indicators allows a wide and deep knowledge of thermal and visual comfort on a daily, monthly or seasonal basis, and it can orient the definition of optimum solutions. This simplified approach requires – as input data – only the hourly operative temperature and the hourly average daylight illuminance to manage a visual and thermal comfort analysis. It may have a large application since it can be used whenever an effective and quick comparison among several technical solutions has to be made; this can happen during the design phase for both new and existing buildings. Thanks to the wide range of application, the same approach is currently being adopted by the authors to evaluate the effectiveness of new materials (PCMs, VIP, etc.) and components (overhangs, venetian blinds, etc.) as well as for setting ventilation strategies; the results of such applications will be reported in following papers. References [1] P.O. Fanger, Thermal Comfort—Analysis and Applications in Environmental Engineering Copenhagen, Danish Technical Press, 1970. [2] SO Standard 7730, 1994, Moderate thermal environments—Determination of the PMV and PPD indices and specification of the conditions for thermal comfort, revised in 2005. [3] J.F. Nicol, M.A. Humphreys, Thermal comfort as part of a self-regulating system, in: Proceedings of the CIB Symposium on Thermal Comfort, Building research Establishment, Watford, UK, 1972. [4] R.J. de Dear, G.S. Brager, Thermal comfort in naturally ventilated buildings: revisions to ASHRAE Standard 55, Energy and Buildings 34 (2002) 549–561. [5] J.F. Nicol, M.A. Humphreys, Adaptive thermal comfort and sustainable thermal standards for buildings, Energy and Buildings 34 (2002) 563–572. [6] ASHRAE Standard 55, 2004, Thermal Environmental Condition for Human Occupancy, Atlanta, ASHRAE Inc. [7] EN Standard 15251, 2007, Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics. [8] N. Djongyang, R. Tchinda, D. Njomo, Thermal comfort: a review paper, Renewable and Sustainable Energy Reviews 14 (2010) 2626–2640. [9] EN Standard 12464-1, 2002, Light and lighting – lighting of work places - Part 1: indoor work places. [10] EN Standard 15193, 2007, Energy performance of Buildings—Energy requirements for lighting. [11] C.F. Reinhart, O. Walkenhorst, Dynamic radiance-based daylight simulations for a full-scale test office with outer venetian blinds, Energy and Buildings 33 (2001) 683–697. [12] C.F. Reinhart, J. Mardaljevic, Z. Roger, Dynamic daylight performance metrics for sustainable building design, Leukos 3 (July (1)) (2006) 1–25. [13] A. Nabil, J. Mardaljevic, Useful daylight illuminance: a new paradigm to access daylight in buildings, Light Research & Technology 37 (2005) 41–59. [14] A. Nabil, J. Mardaljevic, Useful daylight illuminances: a replacement for daylight factors, Energy and Buildings 38 (2006) 905–913. [15] Z. Roger, Daylight Metric Development Using Daylight Autonomy Calculations in the Sensor Placement Optimisation Tool, Boulder, Colorado, USA, 2006. [16] J.F. Nicol, M.A. Humphreys, Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN15251, Buildings and Environment 45 (2010) 11–17. [17] Y. Zhang, K. Lin, Q. Zhang, H. Di, Ideal thermophysical properties for free-cooling (or heating) buildings with constant thermal physical property material, Energy and Buildings 38 (2006) 1164–1170. [18] US Department of Energy, Energy Plus version 6.0, 2010, http://apps1.eere. energy.gov/buildings/energyplus.