impact of clothing and activity level on energy...

Impact Of Clothing and Activity Level On Energy Consumption and

Thermal Comfort On The Occupants In The Residential Building In

Cold climate Region.

Sadaf Alam1,*

1 Department of Energy Technology, School of Engineering, Aalto University, Finland

ABSTRACT

In this paper, various clothing level and metabolic rates have been simulated and

analyzed to study the impact on the thermal comfort and energy efficiency of the

detached house in cold climate region Finland.

The main objective of this paper is to show how much minimum and maximum

indoor air temperature can be achieved while fulfilling the target values for thermal

conditions selected and defined according to SFS-EN—15251. PMV and PPD have

been calculated in order to show the satisfaction crieterias.

KEYWORDS

Thermal comfort, PMV, PPD

INTRODUCTION

Occupant’s comfort role has risen further in relative terms, as lighting, building

envelopes, and heating, ventilation, and air-conditioning (HVAC) equipment have

improved in efficiency; meanwhile comfort expectations have increased (D. Kaneda et

al. 2010 , P. Hoes et al. 2009)

Employing efficient building techniques can go a long way in keeping the electricity

costs down, long term economic and infrastructure benefits. However, Occupant’s

comfort is major need and concern for evaluating the performance of a building

control system, since a poor indoor comfort can directly effect on productivity and

efficiency as described in (ASHRAE, 2010).

(ASHRAE, 2010) says, the amount of thermal insulation worn by a person has a

substantial impact on thermal comfort (Clothing adjustment is a behaviour that directly

affects the heat-balance. The thermal insulation provided by garments and clothing

ensembles is expressed in a unit named clo, where 1 clo is equal to 0.155 m2 K/W. For

near-sedentary activities where the metabolic rate is approximately 1.2 met, the effect

* Corresponding author email: [email protected]

657

of changing clothing insulation on the optimum operative temperature is approximately

6 °C per clo. Clothing adjustment is perhaps the most important of all the thermal

comfort adjustments available to occupants in office buildings (Newsham GR. 1997)

As mentioned by (Fanger .1997) , Clothing is one among the six variables (others are:

Air temperature, mean radiant temperature, air speed, relative humidity and metabolic

activity) that affects the calculation of the predicted mean vote (PMV) and predicted

percentage of dissatisfied (PPD) and therefore is an input for thermal comfort

calculations according to (ASHRAE .2010 ) , European (ISO. ISO 7730. 2005) and

International thermal comfort standards. The selection of the clothing insulation for

thermal comfort calculations affects the design (sizing and analysis) of HVAC systems,

the energy evaluation and the operation of buildings. Previous attempts to develop a

dynamic clothing model demonstrated that the ability to more accurately predict

variations in clothing leads to improved thermal comfort (Newsham GR.. 1997),

smaller HVAC size and lower energy consumption (De Carli M et al. 2007). (De Carli

M et al. 2007), concluded that in mechanically conditioned buildings a variation of

0.1 clo is sufficient to significantly affect the comfort evaluation based on the

PMV–PPD model.

Although there are studies (De Carli M, et al 2007, De Dear R et al. 1997, Faraway JJ.

2006 and Morgan C, et al. 2003) that has addressed clothing insulation in mechanically

ventilated buildings, however the thermal comfort of the occupants has not been

adequately addressed and discussed. We attempt to fill this gap by addressing the

acceptable range of the operative temperature and indoor air temperature to maintain

the thermal comfort of the occupants.

RESEARCH METHODOLOGY AND ASSUMPTIONS

Fanger approach

In our present study we have used ( Fanger 1970 ) approach to predict the thermal

performance of the building. Study compares the (Predicted Mean Vote (PMV) index

on 7 point thermal sensation scale, which is being calculated using the effective

operative (ISO7730:2005) and air temperatures. Thermal comfort has a great

influence on the productivity and satisfaction of indoor building occupants (Roberto

et al. 2007).

Following Table 1 shows, the thermal sensation scale of the thermal comfort

following Fanger, quantified by an adapted ASHRAE 7 – point scale

Table 1: The 7-Point Thermal Sensation Scale (Fanger .1970)

PMV Scale Description

-3 Cold

-2 Cool

658

-1 Slightly cool

0 Neutral

1 Slightly warm

2 Warm

3 Hot

(Fanger .1970) realized that the vote predicted was only the mean value to be

expected from a group of people, and he extended the PMV to predict the proportion

of any population who will be dissatisfied with the environment.

The Predicted percentage dissatisfied (PPD)-index those who vote outside the range

of -1 (slightly cool to + 1 (slightly warm) scaling points were termed as dissatisfied.

The distribution of PPD is based on observations from climate chamber experiments

and not from field measurements.

Fanger related the PPD index to the PMV index as follows

�� = 100 − 95�( . �� .��)

(1)

This relation has been represented in the figure 1

Figure1. Predicted Percentage of Dissatisfaction (PPD) as a function of Predicted

Mean Vote (PMV) (Fanger,1970)

Figure 1 it can be seen that when PMV index is in between -0.5 and + 0.5, it means

less than 10% will find the thermal environment unacceptable. It can be further seen

from this curve that the minimum PPD is 5 % when PMV value is 0.

Standards relating to this study

In this study we have used two main reference standards SFS- EN 15251 and

ASHRAE- 55 0 0

0

20

40

60

80

-4 -2 0 2 4

PP

D %

PMV

Predicted percentage of dissatisfied (PPD) as a function

of predicted mean

vote (PMV)

PPD %

659

SFS-EN 15251

This European standard (SFS- EN 15251) specifies the indoor environmental

parameters which have an impact on energy performance of the buildings. Table 2 and

table 3, show the thermal comfort requirements for different categories of

environment and types of space.

Table 2: Description of the applicability of the categories used (SFS EN ISO 15251,

2007)

Category Explanation

I High level of expectation and is recommended for spaces occupied by very

sensitive and fragile persons with special requirements like

handicapped, sick, very young children and elderly persons

II Normal level of expectation and should be used for new buildings and

renovations

III An acceptable, moderate level of expectation and may be used for existing

buildings

IV Values outside the criteria for the above categories. This category should

only be accepted for a limited part of the year

Table 3: Comfort categories valid for mechanically heated and cooled buildings (SFS

EN ISO 15251, 2007)

Category Thermal state of the body as a whole

Predicted percentage of dissatisfied PPD % Predicted Mean Vote

I < 6 -0.2 < PMV < +0.2

II < 10 -0.5 < PMV < +0.5

III < 15 -0.7 < PMV < +0.7

I V > 15 PMV < - 0.7 or +0.7 < PMV

ASHRAE- 55

In our study we have used table 4 ) ASHRAE s-55 , 2010) to define the maximum

change in Operative temperature allowed during a period of time.

Table 4: Limits on Temperature Drifts and Ramps

Time Period, h 0.25 0.5 1 2 4

Maximum Operative

Temperature , °C 1.1 1.7 2.2 2.8 3.3

660

This table 4 explains that the , operative temperature (Top) may not change more than

2.2°C during a 1.0 h period, and it also may not change more than 1.1°C during any

0.25 h period within that 1.0 h period. If variations are created as a result of control or

adjustments by the user, higher values may be acceptable.

Building Simulation tool IDA ICE

In this paper for our study we have used IDA ICE building simulation software

(Sahlin P ,1996 and Björsell N). IDA Indoor Climate and Energy (IDA ICE) is a

whole year detailed and dynamic multi-zone simulation application for the study of

indoor climate as well as energy. Different case studies have been validated IDA ICE

(Moinard S et al. 1999)

Weather Data and Location

In our study, Finnish test reference year (TRY2012) is being used as a weather data

for energy simulations. Finland belongs wholly to the temperate coniferous-mixed

forest zone with cold, wet winters. The annual average temperature for Helsinki –

Vantaa region is + 5.4°C (Targo Kalameesa, et al. 2012) and it comes under climate

zone 1. The average number of degree days (at indoor temperature 17) is 3952.

Building description

In this paper we have simulated Finnish single family detached house having heated

area of 180 m2

and air volume of 468 m3 The building has major four occupied zones,

U-values and air tightness of the 1960 Light weight case based on the default values of

the statement of Finnish energy certificate 2013.

We have taken the activity levels (according to SFS EN ISO 15251) of 1 met (Seated

and relaxed) and 1. 2 met (Standing and relaxed) and clothing insulation levels of 0.96

clo (Trousers, long sleeved shirts plus suit jackets) and 1.14 clo (Trousers, long

sleeved shirts plus suit jackets plus vest and T- shirt).

RESULTS AND DISCUSSION

In this study we have done hourly dynamic simulation on IDA ICE and analyzed

building cases with different clothing and activity level. Fanger approach has been

applied to predict the thermal performance of the buildings. An example has been

showed in figure2.

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Figure 2. Minimum Top and Minimum Tair at different levels of thermal insulation

Above figure 2 shows the minimum operative temperature (top) and air tem

(tair) at different levels of thermal insulation fulfilling the comfort conditions for air

conditioned buildings mentioned in SFS

no thermal comfort violations, and then we have calculated the minimum o

temperatures at different level of thermal comfort which has been showed and

discussed in the below tables

level and clothing level.

Table 5: Min Top and min Tair of 1960 LW at different activity and clothing level

Category

PPD

PMV

1960 L

Min

Top

I

II

III

< 6

< 10

< 15

-0.2<PMV<+0.2

-0.5<PMV<+0.5

-0.7<PMV<+0.7

23.5

22.4

19.6

To implement this, the coldest period (8th of January

determine critical values of PMVs (minimum and maximum) and indoor temperatures.

As the results of this strategy, PMVs and indoor temperature are drawn to find linear

trendline of PMV vs indoor temperature.

increased amount of activity and clothing levels can help in decreasing the operative

temperature in certain amount approximately by 0.5

-0.9-0.8-0.7-0.6-0.5-0.4-0.3-0.2-0.1

00.10.20.30.40.50.60.70.80.9

20 21

PM

V

PMV value

Linear line of maximum PMV

Minimum Top and Minimum Tair at different levels of thermal insulation

shows the minimum operative temperature (top) and air tem


ed buildings mentioned in SFS-EN 15251 standard. We can see that there are

no thermal comfort violations, and then we have calculated the minimum o


discussed in the below tables 5 and 6 for different building cases at different

Min Top and min Tair of 1960 LW at different activity and clothing level

1960 LW 1 met 1960LW 1.2 met

0.96 clo 1.14 clo 0.96 clo

Min

Top ◦C

Min

Tair

◦C

Min

Top

◦C

Min

Tair

◦C

Min

Top ◦C

Min

Tair

◦C

23.5

22.4

.6

24.2

23.1

22.3

22.9

21.6

20.7

23.4

22

21.1

22

20.5

19.5

22.3

20.8

19.8

To implement this, the coldest period (8th of January-4th of March) was simulated to



trendline of PMV vs indoor temperature. From table 5, results shows that


temperature in certain amount approximately by 0.5 ◦C.

PMV = 0.205AT - 4.71

22 23 24 25 26

Air temperature

Linear line of minimum PMV

Linear line of maximum PMV Linear (PMV value)

Minimum Top and Minimum Tair at different levels of thermal insulation

shows the minimum operative temperature (top) and air temperature


can see that there are

no thermal comfort violations, and then we have calculated the minimum operative


for different building cases at different activity

Min Top and min Tair of 1960 LW at different activity and clothing level

1960LW 1.2 met

1.14 clo

Min

Top ◦C

Min

Tair ◦C

20.8

19.2

18.2

21.1

19.5

18.4

ch) was simulated to



results shows that, by


26

662

Table 6: Comparison of Min and Max Operative and Air temperatures for 1960LW

(1.2 met, 0.96 clo) with electrical radiators with air velocity= 0.1 m/sec

Category

PPD

PMV

1960 LW_1.2 met, 0.96 clo 1960 LW_1.2 met, 0.96 clo

Electric radiators , V= 0.1m/sec Electric radiators , V= 0.1 m/sec

Min Top ◦C Min Tair

◦C

Max Top ◦C

Max Tair ◦C

I

II

III

< 6

< 10

< 15

-0.2<PMV<+0.2

-0.5<PMV<+0.5

-0.7<PMV<+0.7

22

20.5

19.5

22.3

20.8

19.8

23

24.4

25.3

23.3

24.7

25.6

From the table 6, it can be seen that the maximum operative temperature can be 25 ◦C

and minimum can be 19.6 ◦C approximately in 1960 light weight buildings having

electric heating systems.

CONCLUSION

This study presented acceptable range of indoor air and operative temperatures of a

detached house in a cold climate of Finland fulfilling thermal comfort categories

recommended by SFS-EN 15251 standard. The amount of temperature decrease

depends on activity and clothing levels of occupants, air velocity, building properties

such as heat distribution system, thermal insulation, and thermal mass.

ACKNOWLEDGEMENTS

I would like to dedicate my acknowledgment of gratitude towards my instructor and

professor who gave me an opportunity to work on SAGA project.

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