Journal of the Chinese Institute of Engineers, Vol. 28, No. 4, pp. 579-588 (2005) 579

DEVELOPMENT OF SOLAR COOLING LOAD FACTORS FOR

FENESTRATION IN THAILAND

Somsak Chaiyapinunt*, Khemmachart Mangkornsaksit, and Boonyarit Phueakphongsuriya

ABSTRACT

This article describes the development of solar cooling load factors (SCL) forcalculating cooling load from the fenestration part of the building envelopes in Thai-land using Bangkok weather data. The Bangkok weather data are selected from 12years of data collected by the meteorological department. Two sets of weather dataare chosen based on dry bulb temperature of 0.4% annual cumulative frequency ofoccurrence and based on dry bulb temperature of 0.4% hourly cumulative frequencyof occurrence and solar radiation obtained from the ASHRAE mathematical model.The building parameters that have effects on the room thermal response are studied.288 different room types were checked. The values of amplitude and delay based onsolar weighting factors are analyzed. Then, rooms with similar thermal response aregrouped together and represented by a single point for the group. Each group is de-fined as a single zone type. Four different zone types are established. For each set ofweather data, the values of solar cooling load factors for each zone type are developed.

Key Words: solar cooling load, fenestration, building, Thailand.

*Corresponding author. (Tel: 662-2186610; Fax: 662-2522889;Email: fmescy@eng.chula.ac.th)

The authors are with the Mechanical Engineering Department,Faculty of Engineering, Chulalongkorn University, Bangkok10330, Thailand.

I. INTRODUCTION

Large office and commercial buildings in Thai-land usually have a large number of glass windowsinstalled as parts of the building envelopes. The glasswindows are installed to serve as physical and visualconnection to the outside, as well as to make build-ings look more aesthetic. And since Thailand is acountry where the weather is hot and humid most ofthe year, the glass windows installed in buildings inThailand also act as a means to admit solar radiationinto buildings and convert it into building coolingload. Such buildings which are air conditioned willusually consume more air conditioning energy to takecare of the cooling load due to the large amount ofsolar radiation passing through glass windows. Tobe able to predict an accurate cooling load for abuilding, especially the solar load part, for sizingcooling equipment, would help designers to achievemore efficient air conditioning systems in terms ofenergy usage and thermal comfort. Building cooling

load is dependent on local weather data, thermal char-acteristics of material used for building envelope, andbuilding usage. In order to accurately calculate thebuilding cooling load, it usually requires a large andcomplex energy simulation computer program suchas DOE 2.1E which uses the transfer function methodto calculate the cooling load. Though DOE 2.1E isquite a powerful and accurate simulation program, itrequires local annual weather data (8760 hours) andrequires a complex and lengthy data input. Therefore,DOE 2.1E is not terribly popular with most designers,who prefer a more compact and easier to use tool forcalculating cooling load. The cooling load tempera-ture differences, solar cooling load factors, and in-ternal cooling load factors (CLTD/SCL/CLF) methodis a simplified transfer function method (TFM) thatwas first presented in ASHARE (1977). This methodmakes hand calculation of cooling load possible bymaking use of the developed CLTD, SCL and CLFvalues. For the cooling load caused by solar radia-tion passing through the fenestration of the buildingenvelope, ASHRAE (1997a) has developed SCLvalues based on solar radiation variation typical of40° N latitude on July 21, with certain outside andinside air temperature conditions, to calculate for thatcooling load. The accuracy of the values of solar

580 Journal of the Chinese Institute of Engineers, Vol. 28, No. 4 (2005)

cooling load factors (SCL) given by ASHRAE(1997a) could be in question when the location ofbuilding is not at 40°N (especially below 24°N).

The purpose of this article is to describe the de-velopment of solar cooling load factors for fenestra-tion used in building envelopes in Thailand usingBangkok (latitude 13.7°N) weather data. The devel-oped solar cooling load factors shall be used to calcu-late the building cooling load due to solar heat gainthrough fenestration. With these SCL values that arespecifically developed from local weather data, thecooling load of buildings with fenestration in Thailandcan be easily manually performed with more accuracy.

II. COOLING LOAD DUE TO HEAT GAINTHROUGH FENESTRATION

The cooling load for a building results from foursources: conductive heat gain through surfaces suchas windows, walls, and roofs; solar heat gain throughfenestration; internal heat gain from lights, people,and equipment; and heat gain from infiltration. Fen-estration usually means any aperture in a buildingenvelope. Fenestration components include glazingmaterial, either glass or plastic, external shadingdevices, and/or internal shading devices. The trans-fer function method (TFM), proposed by Mitalas(1972) used for calculating the cooling load, uses atwo step procedure. First TFM establishes the heatgain from all sources by applying a series of weight-ing factors to calculate the heat gain and then con-verting such heat gain to cooling load by a secondseries of weighting factors or so called coefficientsof room transfer function. The CLTD/SCL/CLFmethod is a simplified TFM for direct one step cal-culation of cooling load. Using this method to calcu-late cooling load from fenestration, the heat gain isdivided into radiant and conductive loads. The cool-ing load due to conduction is expressed as

Qcond = UA (CLTD) (1)

where U = overall heat transfer coefficient forsurface, W/m2 - °C

A = area of surface, m2

CLTD = cooling load temperature difference,°C

The cooling load due to solar radiation trans-mitted through and absorbed by the fenestration isdetermined by

Qrad = A(SC) SCL (2)

where A = area of fenestration, m2

SC = shading coefficientSCL = solar cooling load factor, W/m2

The total cooling load from fenestration is thenthe sum of the conductive and radiant componentsQcond and Qrad.

The solar cooling load factor (SCL) for a par-ticular room is dependent on weather data, orienta-tion of fenestration surface to the sun, and internalroom parameters.

III. WEATHER DATA

1. Weather Data Based on 0.4% Annual Cumula-tive Frequency of Occurrence

The weather data for a day used for calculatingSCL values are selected from 12 years (1988 – 1999)of Bangkok weather data collected by the meteorologi-cal department. The selection is done based on consid-ering the most influential parameters on the cooling loadwhich are solar radiation and dry bulb temperature. Theselected 0.4% annual cumulative frequency of occur-rence for dry bulb temperature and global radiation assuggested by ASHRAE (1997b) are chosen. The val-ues of ambient dry bulb temperature and solar globalradiation corresponding to 0.4 annual percentiles rep-resent the value that is exceeded on average by 0.4% ofthe total number of hours in a year (8760). The 0.4%value of dry bulb temperature is the value at the 35thhour ((0.4/100) × 8760) of the annual data. The aver-age value of dry bulb temperature at 0.4% annual cu-mulative frequency of occurrence of 12 years data is36°C with the average mean daily range of 7.72°C. Thenthe values of design hourly dry bulb temperature in aday are obtained by the following relationship as

To = Td – DrX (3)

where To = hourly dry bulb temperature, °CTd = maximum dry bulb temperature, °CDr = mean daily range (7.72 °C)X = percentile of daily variation of dry bulb

temperatureThen the mean coincident of solar radiation and

related weather data are obtained. The 24 hour drybulb temperature with its coincident weather data arearranged as weather data for a design day.

The second set of weather data shall be selectedbased on the solar global radiation. The solar globalradiation data are only collected in day time with 15hours in a day (5475 hours in a year). The 0.4% an-nual cumulative frequency of occurrence for globalradiation shall be the values at the 22nd hour ((0.4/100) × 5475). The average values of 0.4% annualcumulative frequency of occurrence for global radia-tion of 12 years data was 1021 watt per square meter.Then the average values of the global radiation andits coincident dry bulb temperature and other related

S. Chaiyapinunt et al.: SCL for Fenestration in Thailand 581

weather data in the rest of the day are obtained fromthe data on the selected day. In order to use DOE2.1E to accurately calculate building cooling load, theweather data input have to be in the Typical Meteo-rological Year (TMY) format. This format requiresthe solar radiation data input in 3 components: global,direct normal, and diffuse radiation components. Thediffuse and direct normal radiation components canbe obtained by using the mathematical model sug-gested by Chaiyapinunt and Mangkornsaksit (2000)applied to the measured global radiation.

The cooling loads of the selected building cal-culated by DOE 2.1E, using two weather data sets,are compared. The one which gives a greater valueof cooling load will be chosen. Therefore the weatherdata selected based on dry bulb temperature of 0.4%annual cumulative frequency of occurrence and itscoincident weather data are chosen as relevantweather data. The dry bulb temperature, global, di-rect normal, and diffuse radiation of the chosenweather data are shown in Fig. 1.

2. Weather Data Based on 0.4% Hourly Cumula-tive Frequency of Occurrence

There is another method to find weather data usedfor calculating cooling load to ensure predicting amaximum building cooling load in a year. The methodis adopted from the so called TAC method (TechnicalAdvisory Committee of ASHVE, a former organiza-tion of ASHRAE) as suggested by Takeda (1990/1991)using cumulative frequency of hourly data over sev-eral years. In this study, the method is modified by

selecting the data based on 0.4% hourly cumulativefrequency of occurrence for the whole 12 years data.The selection is done by rearranging the measureddata (dry bulb temperature, global radiation) at eachhour in a day (i.e., say at 11 o’clock) for the whole12 years from maximum value to minimum value andchoosing value at 0.4% from the maximum value. Onewill get a set of 24 hour dry bulb temperatures and aset of 24 hour global radiation readings. Then, thecoincident weather data for each set of chosen dataare selected. It turned out that with this kind of se-lecting method the distribution of coincident weatherdata with chosen data has an irregular pattern, espe-cially the dry bulb temperature values, which are co-incident with the selected global radiation values.Therefore, in this study, the 24 hours selected dry bulbtemperatures based on 0.4% hourly cumulative fre-quency of occurrence are chosen as relevant weatherdata. To eliminate the problem of poor coincidentweather data, the coincident solar data are obtainedfrom the ASHRAE mathematical model of a clearday condition based on April 21 (April is the hottestmonth in Thailand). The maximum dry bulb temperaturein the considered weather data is 37.2°C. The se-lected weather data, dry bulb temperature, global, directnormal, and diffuse radiation, are shown in Fig. 2.

IV. PARAMETRIC STUDY ON COOLINGLOAD DUE TO SOLAR RADIATION

THROUGH FENESTRATION

In this study, we will emphasize only the cool-ing load due to solar radiation transmitted through

1200

1000

800

600

400

200

0

80

70

60

50

40

30

20

10

0161412

Hour

Global radiationDirect normal radiationDiffuse radiationDry bulb temperature

1086420 24222018

Sola

r ra

diat

ion

(W/m

2 )

Deg

ree

C

Fig. 1 Weather data based on dry bulb temperature of 0.4% an-nual cumulative frequency of occurrence and its coinci-dent solar radiation data. (First set of weather data)

1200

1000

800

600

400

200

0

80

70

60

50

40

30

20

10

0161412

Hour

Global radiationDirect normal radiationDiffuse radiationDry bulb temperature

1086420 24222018

Sola

r ra

diat

ion

(W/m

2 )

Deg

ree

C

Fig. 2 Weather data based on dry bulb temperature of 0.4% hourlycumulative frequency of occurrence and solar radiationfrom ASHRAE mathematical model. (Second set ofweather data)

582 Journal of the Chinese Institute of Engineers, Vol. 28, No. 4 (2005)

and absorbed by fenestration. A 3 mm. clear glass ischosen to represent the fenestration in this study. Theconcept of calculating cooling load by using SCLvalues is to simplify the TFM method into a productof SCL values and a product of A and SC as shown inEq. (2). The cooling load due to solar radiation cal-culated using the TFM method is based on its weight-ing factors suggested by Kerrisk (1981) to convertthe solar heat gain to cooling load for each type ofroom construction, geometry, and decoration.Therefore, the study of the cooling load for differentroom construction, geometry, and decoration can bealso done by studying the variations of its weightingfactors. 13 parameters describing room construction,geometry, and decoration are analyzed in order toassess their effect on room thermal response whencompared to other parameters as suggested by Sowell(1985b). They are room geometry, room height, roomlocation, number of exterior walls, exterior wallconstruction, percentage of glass on the exterior wall,partition type, degree of interior shading, mid-floortype, floor covering, roof type, ceiling type, andfurniture. These parameters and variations in eachone are shown in Table 1. The number of variationson each parameter is listed under the heading of“Level” in Table 1. These parameters are varied sys-tematically so that all possible combinations of theseparameters are studied. It was found from Sowell(1984) under ASHRAE project 359-RP and Sowell(1988a) that the exterior wall construction, percent-age of glass on the exterior wall, and roof type havesmall effect on room thermal response when com-pared to other parameters. These parameters aredropped out from the parametric study. The buildingenvelope chosen for this study is shown in Table 2.The combination of the rest of the parameters and

their variation give a total 288 different roomconditions. The next thing is to minimize the num-ber of room conditions by grouping the room condi-tions that have similar thermal responses together.The room thermal response can be studied by usingthe pair of numbers that represent amplitude and timedelay of the cooling load for a sinusoidal heat gain of1 unit amplitude in a 24-hour period. (as suggestedby Sowell (1985a, 1988b) and Kerrisk (1981)). Therelated equations are as follows

Qt = voqt + v1qt – 1 + v2qt – 2 – w1Qt – 1 – w2Qt – 2

(4)

where Qt = cooling load at time t, Wvi, wi = coefficient of room transfer function

or weighting factorsi = indexqt = hourly heat gain at time t, W

and q = qmax sin(πt/12) (5)

Q/qmax = r = asin(πt/12 – φ) (6)

where Q = cooling load, Wq = hourly heat gain, Wqmax = maximum heat gain of magnitude 1

Watta = amplitudeφ = phase lag (radians)r = dimensionless cooling load

and now consider the two times t = 0 and t = 6 hours

r0 = –asinφ (7)

Table 1 Room parametric level definitions

No. Parameters Levels Description

1 Room geometry 1 4.57 × 4.57 m 2 Room height 1 3 m 3 Room location 2 mid floor, top floor 4 Number of exterior walls 1 1 exterior wall 5 Exterior wall construction 7 7 exterior wall types 6 Percentage of glass on the exterior wall 2 50%, 90% 7 Partition type 2 concrete block with cement plaster,

gypsum board with 100 mm air gap 8 Interior shade compared to glass area 3 0% 50% 100% 9 Floor type 3 75 mm, 125 mm, 200 mm concrete10 Floor covering 2 carpet with rubber pad, vinyl tile11 Roof type 3 3 roof types12 Ceiling type 2 10 mm gypsum board, w/o ceiling13 Furniture 2 with, without

S. Chaiyapinunt et al.: SCL for Fenestration in Thailand 583

r6 = acosφ (8)

a = (r02 + r6

2)1/2 (9)

φ = arc tan(–r0/r6) (10)

d = 12φ/π (11)

where d = time delayThe room weighting factors in the solar radia-

tion part (solar weighting factor) of the building en-velope shown in Table 2 for 288 room conditions arecalculated by using DOE 2.1E. Then, the amplitudeand delay (Eq. 9 and Eq. 11) for each room are calcu-lated for all 288 rooms. The magnitude of the ampli-tude and delay of 288 rooms are plotted in Fig. 3.Each room defined by a particular combination ofparameters shown in Table 1 has a thermal responsethat may be different from others. However, in orderto avoid having to calculate SCL values for each room(288 rooms), it is desirable to somehow identifyrooms that have similar responses and group themtogether into a small number of room types. Roomsthat have values of amplitude and delay close togetherhave similar thermal response and can be grouped andrepresented by a single point for the group. A roomin a particular group will have error associated withit proportional to its distance from its representativepoint in the amplitude and delay plot. With the nor-mal engineering accuracy goal of ±10% of actualvalue and based on hourly calculation, Sowell (1985a,1988c) suggested that the criteria for accepted errorshall be 0-20% for amplitude and ±1/2 hour for delay.This suggests a rectangle with a lower bound no less

than 80% of the upper bound and the horizontal di-mension of the rectangle shall be 1 hour (±1/2 hour).The rectangles are drawn with the intention to coverall points shown in Fig. 3 by having the width of therectangle equal to 1 hour delay time and the height ofthe rectangle equal to 20% of the maximum ampli-tude of the points contained in that rectangle. Then asingle point is selected to represent all the data ineach rectangle. The data point in each rectanglewhich has the smallest deviation from the top cen-troid point (middle point on the upper line of therectangle) of each rectangle is chosen as a represen-tative point. Fig. 4 shows the rectangles on an am-plitude and delay plot and the representative points.Almost every amplitude and delay value of solarweighting factors for 288 rooms fall into fourrectangles. Only very few points are out of these rect-angles and they are still very close to the rectangles.Therefore, four zone types (four rectangles); type A,B, C, D, can be adopted to represent all 288 room

Table 2 Building envelope and its properties

Mass per unitU

Building envelope Structure wall area(W/m2-°C)

(kg/m2)

Wall type 1 Wall of Brick with cement finishing 246.0 1.222-10 mm. cement plaster+150 mm.brick + 10mm. cement plaster

Roof type 1 (ceiling) 100 mm concrete slab with insulation 252.5 0.391-100 mm concrete + 100 mm air gap + 75 mmglass fiber + 10 mm gypsum board

Glass 3 mm clear glass 7.0 5.678

Partition type 1 Concrete block with cement plaster finishing 82.3 1.333-12.5 mm cement plaster + 75 mm concreteblock+ 12.5 mm cement plaster

Partition type 2 Gypsum board with air gap 16.0 1.091-10 mm gypsum board + 100 mm air gap+10 mm gypsum board

1.000.900.800.700.600.500.400.300.200.100.00

0.00 0.20 0.40 0.60 0.80 1.00

Delay in hours

1.20 1.40 1.60 1.80 2.00

Am

plitu

de

Fig. 3 Amplitude and delay obtained from solar weighting fac-tors for 288 room conditions.

584 Journal of the Chinese Institute of Engineers, Vol. 28, No. 4 (2005)

conditions. The representative amplitude and delayvalues for four zone types and their solar weightingfactors which have been previously calculated by us-ing DOE2.1E are shown in Table 3.

V. SOLAR COOLING LOAD FACTORS ANDTHEIR ACCURACY

After specifying the represented weighting fac-tors for each type of room zone, the room coolingload due to solar radiation through fenestration foreach set of weather data can be calculated by usingDOE 2.1E. Then the SCL values for each hour at acertain orientation can be obtained by dividing thecalculated cooling load by the product of shadingcoefficient for surface and area of surface. The SCLvalues based on the first set of weather data (0.4%annual cumulative frequency of occurrence) are shownin Table 4 and SCL values based on the second set ofweather data (0.4% hourly cumulative frequency ofoccurrence) are shown in Table 5. The SCL valuesshown are based on standard clear glass of 3 mm thick-ness with no inside shade (SC = 1), inside air tem-perature of 25°C, outside surface film resistance of0.058 m2-°C/W, and inside surface resistance of 0.121 m2-°C/W. The criteria for selecting zone type touse with SCL values is also shown in Table 6.

The comparison between the results of coolingload due to solar radiation using SCL values devel-oped from the first set of weather data and the

second set of weather data are shown in Fig. 5 for dem-onstration purposes, using east and west orientationof room zone type A having glass window area of 12square meters. The cooling load values due to solarradiation through windows, calculated from both setsof weather data, are in the same pattern with the val-ues calculated from the second set of weather data givinglarger values. The maximum cooling load value dueto solar radiation on a glass window facing east oc-curs in the morning while the maximum cooling loadvalue due to solar radiation on a glass window facingwest occurs in the afternoon. The magnitudes of thesolar cooling load through the west window are greaterthan the solar cooling load through the east window,especially the solar cooling load calculated from thefirst set of weather data. The smaller value of the eastwindow solar cooling load is due to the lower value ofthe direct normal radiation of the first set of the weatherdata in the morning compared to the radiation data inthe afternoon as shown in Fig. 1. The direct normalradiation data of the second set of weather data, is rathersymmetrical around 12 o’clock noon. Therefore, themaximum value of the east and west solar cooling load,calculated from the second set of weather data, are quiteclose together. Then the SCL values of zone type Afrom ASHRAE (1997a) are selected for finding thesolar cooling load of the specified glass window. Theresults are shown with the previous results in Fig. 6and Fig. 7. Some discrepancies in solar cooling loadvalues between ones calculated from ASHRAE’s SCLand the developed SCL can be obviously seen. Fig. 6shows the comparison of the solar cooling load calcu-lated from SCL values based on the first set of weatherdata and SCL values based on ASHRAE. The solarcooling load calculated from SCL values based onASHRAE is obviously larger when compared to theload calculated from the developed SCL values. Fig.7 shows the comparison of the solar cooling load cal-culated from SCL values based on the second set ofweather data and SCL values based on ASHRAE. Thediscrepancies in solar cooling load values have a similarpattern to the ones shown in Fig. 6, except that thedifference in the values are not as large as in Fig. 6.From Fig. 6 and Fig. 7, one can clearly see that somelarge error in the solar cooling load calculated fromASHRAE exists. Therefore, it would be more

Table 3 Solar weighting factors of the representative point in each room zone type

Zone No.Amplitude Delay v0 v1 v2 w1 w2type plots

A 162 0.754 0.596 0.63071 -0.84027 0.25935 -1.44138 0.49811B 98 0.620 0.761 0.54295 -0.62371 0.13722 -1.25355 0.31753C 15 0.633 1.651 0.33452 -0.35483 0.06562 -1.48151 0.53313D 8 0.495 1.437 0.32731 -0.35484 0.06450 -1.39595 0.43884

1.000.900.800.700.600.500.400.300.200.100.00

0.00 0.20 0.40 0.60 0.80 1.00

Delay in hours

1.20 1.40 1.60 1.80

Am

plitu

de

Zone AZone B

Zone D

Zone C

Fig. 4 Amplitude and delay obtained from solar weighting fac-tors for 288 room conditions and their rectangles with rep-resentative rooms

S. Chaiyapinunt et al.: SCL for Fenestration in Thailand 585

Table 4 Solar cooling load for glass based on first set of weather data

Glass (Zone type A) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 6 5 4 4 3 30 72 87 102 110 114 115 119 119 117 115 104 59 24 18 13 10 8 7NE 6 5 5 4 3 82 160 297 306 256 181 140 130 118 103 84 60 35 21 16 13 10 9 7E 7 6 5 4 4 92 181 353 373 316 207 149 135 122 107 87 62 37 22 17 14 11 9 8

SE 6 5 4 4 3 53 121 221 240 210 156 129 121 112 99 81 57 33 19 14 11 9 8 7S 4 4 3 3 2 15 51 63 85 100 106 109 112 108 96 78 54 30 16 12 9 7 6 5

SW 12 10 8 7 6 18 51 62 81 94 102 112 167 236 293 312 268 130 53 38 28 21 17 14W 18 15 13 11 9 21 54 64 83 95 103 119 229 357 461 513 467 228 88 62 45 35 27 22

NW 15 13 11 9 8 20 53 63 82 96 104 118 193 289 379 432 401 199 76 53 39 30 23 19HOR 22 19 17 15 13 31 124 246 383 498 565 619 632 565 478 344 186 100 66 51 42 35 30 25

Glass (Zone type B) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 15 14 12 11 10 32 68 80 92 99 102 104 108 109 108 107 99 61 32 27 23 21 19 17NE 18 17 15 13 12 79 145 262 268 226 162 130 124 116 105 89 69 48 36 31 28 25 23 20E 21 19 17 15 14 88 164 311 327 277 185 138 130 122 111 94 74 53 40 35 31 28 25 23

SE 16 15 13 12 11 53 111 196 211 185 139 118 114 108 98 83 63 43 31 28 25 22 20 18S 12 10 9 8 8 18 49 58 77 89 95 97 101 98 88 74 54 34 23 20 18 16 14 13

SW 28 26 23 21 19 28 55 63 79 89 96 104 152 211 260 277 240 123 60 50 44 39 35 31W 43 39 35 32 29 37 63 71 86 95 100 114 208 318 407 452 413 211 95 78 68 60 54 48

NW 37 33 30 27 24 33 60 67 83 93 100 112 176 259 336 381 356 184 82 67 58 51 46 41HOR 21 18 16 14 12 25 99 200 316 418 485 537 557 510 442 333 200 118 79 59 46 36 30 25

Glass (Zone type C) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 13 11 9 8 7 20 46 64 79 91 98 103 108 111 112 111 106 81 54 40 31 24 19 16NE 14 12 10 9 7 48 102 195 234 230 195 165 149 135 121 105 85 64 47 37 29 24 20 16E 15 13 11 10 8 54 115 229 282 280 230 187 163 146 129 111 90 68 51 40 32 26 22 18

SE 12 11 9 8 7 33 76 145 181 183 161 142 132 122 111 97 79 59 43 33 26 21 18 15S 10 8 7 6 5 11 32 45 63 78 88 95 100 101 96 85 69 51 36 27 21 17 14 11

SW 27 22 19 16 13 18 37 48 63 76 86 96 130 179 227 259 251 180 119 87 65 50 40 32W 42 35 29 25 21 25 42 53 67 80 89 102 165 255 344 409 416 301 196 142 106 81 64 51

NW 36 30 25 21 18 22 40 51 66 79 89 101 146 213 286 344 354 259 168 122 91 69 55 44HOR 58 50 44 38 33 39 88 163 258 351 423 484 521 509 471 396 294 218 169 137 113 94 80 68

Glass (Zone type D) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 22 20 18 17 15 28 52 65 76 84 89 92 96 98 99 99 94 71 48 39 34 30 27 24NE 28 25 23 21 20 59 106 189 213 199 162 136 126 117 108 96 81 64 52 45 40 37 33 30E 31 29 26 24 22 66 120 222 257 243 189 152 137 127 116 103 87 70 57 50 45 41 37 34

SE 24 22 20 19 17 42 81 142 167 161 135 119 112 106 99 88 73 57 46 40 35 32 29 27S 17 16 14 13 12 18 37 47 61 73 80 84 88 88 83 74 60 45 34 29 25 22 20 19

SW 40 37 34 31 28 33 49 58 69 79 86 93 124 167 207 230 216 146 95 74 62 54 49 44W 61 56 51 47 43 46 62 69 80 88 94 104 163 243 317 365 359 243 152 117 97 84 75 68

NW 53 48 44 40 37 40 57 64 76 85 91 101 142 201 263 308 308 210 130 101 83 72 64 58HOR 82 75 69 63 58 63 111 183 270 353 413 462 489 468 427 354 258 192 156 135 120108 98 90

appropriate to use SCL values developed from localweather data for calculating building solar coolingload rather than using SCL values generated fromASHRAE.

VI. CONCLUSION

This article describes the development of solarcooling load factor values for the fenestration in

586 Journal of the Chinese Institute of Engineers, Vol. 28, No. 4 (2005)

Table 5 Solar cooling load for glass based on second set of weather data

Glass (Zone type A) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 4 3 3 3 2 24 64 73 79 86 89 89 92 90 87 86 74 22 16 12 9 7 6 5NE 6 5 5 4 3 115 354 396 353 262 164 128 118 108 97 81 57 26 20 16 13 11 9 7E 8 7 6 5 4 138 437 506 477 373 224 149 132 119 105 87 62 30 23 19 15 13 11 9

SE 6 5 4 4 3 81 272 332 322 262 177 126 116 107 95 80 56 25 19 15 12 10 8 7S 4 3 3 2 2 12 42 62 75 84 89 91 93 90 84 71 49 18 13 10 8 6 5 4

SW 11 10 8 7 6 14 42 61 74 83 88 97 170 262 332 353 281 73 50 36 27 21 17 14W 16 14 12 10 9 17 44 63 76 84 88 96 213 368 486 537 452 110 75 54 40 31 24 20

NW 13 11 9 8 7 15 43 62 75 84 88 90 150 260 365 422 365 87 59 42 31 24 19 15HOR 24 21 18 16 14 24 145 311 457 575 656 693 675 613 508 358 186 93 69 55 45 37 32 28

Glass (Zone type B) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 11 10 9 8 7 26 59 67 72 77 80 81 83 83 81 80 71 27 22 19 17 15 14 12NE 20 18 16 14 13 108 312 346 309 231 150 123 118 112 103 90 70 43 38 33 30 27 24 22E 24 22 20 18 16 130 386 443 416 328 204 144 134 126 116 102 80 52 46 41 37 33 30 27

SE 19 17 15 14 12 78 242 291 282 231 160 119 114 108 100 87 67 41 35 31 28 25 23 21S 10 9 8 7 7 14 40 56 68 76 80 82 84 82 77 67 49 23 19 17 15 13 12 11

SW 28 26 23 21 19 25 48 63 73 80 83 91 154 233 293 311 251 74 58 49 43 39 35 31W 40 36 33 29 26 32 54 69 78 85 87 93 194 327 427 472 399 108 84 71 62 55 50 45

NW 31 28 25 23 21 27 49 65 75 81 84 86 138 232 322 371 323 86 66 56 49 43 39 35HOR 23 19 17 15 13 20 115 251 378 485 563 605 600 555 473 349 204 115 83 62 48 39 32 27

Glass (Zone type C) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 9 8 6 6 5 16 40 54 63 72 77 81 84 85 85 84 78 48 36 27 21 16 13 11NE 14 12 10 9 8 66 210 282 296 262 206 168 147 132 118 103 83 59 45 36 29 24 20 17E 17 15 13 11 9 79 259 358 390 359 279 215 180 156 136 117 95 68 53 42 34 28 24 20

SE 14 12 10 8 7 48 161 232 259 245 202 163 142 128 114 100 81 57 44 34 28 23 19 16S 8 7 6 5 4 9 26 42 56 67 75 80 84 85 82 75 61 40 30 23 18 14 12 10

SW 26 22 18 16 13 16 31 46 59 69 76 84 127 190 251 288 269 159 113 83 63 49 39 32W 38 32 27 22 19 21 36 50 62 72 78 85 151 254 355 425 413 239 170 124 93 72 57 46

NW 30 25 21 18 15 18 33 47 60 70 76 81 115 185 266 329 327 188 134 98 73 57 45 36HOR 63 54 47 41 35 37 99 201 308 408 492 549 571 558 510 424 311 227 180 146 121 101 86 73

Glass (Zone type D) Hour

face 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

N 16 15 13 12 11 22 44 54 60 66 70 72 74 75 75 74 69 41 33 27 24 21 19 17NE 30 27 25 23 21 78 212 263 261 220 166 137 126 117 109 99 83 63 54 48 43 39 36 33E 37 34 31 29 26 94 261 334 345 303 224 172 151 138 127 115 98 76 66 59 53 48 44 41

SE 28 26 24 22 20 59 165 219 231 210 165 132 121 112 105 94 79 60 51 45 40 37 33 31S 14 13 12 11 10 15 31 44 54 62 68 71 74 74 72 65 53 35 28 24 21 19 17 16

SW 40 37 34 31 28 31 45 56 65 72 76 83 122 179 229 255 229 121 90 72 61 54 48 44W 57 52 48 44 40 42 54 65 74 80 83 88 150 243 327 378 353 180 131 104 88 77 69 62

NW 44 41 37 34 31 34 47 59 67 74 78 80 112 177 246 295 282 142 104 82 69 61 54 49HOR 89 82 75 69 63 64 125 222 320 408 478 522 533 513 462 378 273 201 167 146 130 117 107 98

building envelopes, using Bangkok design weatherdata. With these SCL values, the determination ofcooling load from the fenestration of the building

envelopes due to solar radiation can be easily andmanually performed. The SCL values based on thefirst set of weather data are suitable for predicting

S. Chaiyapinunt et al.: SCL for Fenestration in Thailand 587

Table 6 Zone types for use with SCL

Zone parametersZone

Floor CeilingPartition type Interior shading Floor type Furniture type

covering type

Gypsum Carpet 0 or 50 or 100% n/c n/c n/c AGypsum Vinyl tile 0 or 50 or 100% n/c n/c n/c A

Concrete block Carpet 100% n/c n/c n/c AConcrete block Carpet 0 or 50% n/c n/c n/c B

Concrete block* Vinyl tile 0 or 50 or 100% n/c n/c n/c BConcrete block Vinyl tile 0% 75 mm concrete n/c n/c CConcrete block Vinyl tile 50% 75 mm concrete without with CConcrete block Vinyl tile 0% 100 mm concrete without without CConcrete block Vinyl tile 0% 100 mm concrete without with DConcrete block Vinyl tile 0 or 50 % 125 mm concrete without n/c D

Note: n/c means the parameter has no effect,*start with zone type C and D, if the room does not fit in zone type C and D use zone type B

the solar cooling load through glass window for gen-eral usage such as predicting building energy usage,etc, while the SCL values based on the second set ofweather data will be more suitable when the design-ers emphasize peak solar cooling load and the size ofthe air conditioning equipment. The study also showsdiscrepancies in solar cooling load values when oneuses SCL values from ASHRAE (1997a) suitable foruse in North America to calculate the solar coolingload in Thailand. With more accurate values of SCL,the cooling load calculation for solar radiationthrough fenestration can be easily and manually per-formed and yield a more accurate result. This will

8000

7000

6000

5000

4000

3000

2000

1000

00 2 4 6 8 12

Hour

East solar load 1st weatherWest solar load 1st weatherEast solar load 2nd weatherWest solar load 2nd weather

14 16 18 20 22 21 24

Sola

r ra

diat

ion

load

(W

att)

Fig. 5 The comparison between cooling load due to solar radia-tion of specified glass window calculated from SCL val-ues based on 1st weather data set and ones calculated fromSCL values based on 2nd weather data set

allow air conditioning systems design in Thailand tobe performed more easily and more effectively.

ACKNOWLEDGMENTS

The authors are grateful for the financial sup-port from The Thailand Research Fund.

NOMENCLATURE

a amplitudeA area of surface, m2

Fig. 6 The comparison between cooling load due to solar radia-tion of specified glass window calculated from SCL val-ues from ASHRAE and ones calculated from SCL valuesbased on 1st weather data set

8000

7000

6000

5000

4000

3000

2000

1000

00 2 4 6 8 12

Hour

ASHRAE east solar loadEast solar load 1st weatherASHRAE west solar loadWest solar load 1st weather

14 16 18 20 22 21 24

Sola

r ra

diat

ion

load

(W

att)

588 Journal of the Chinese Institute of Engineers, Vol. 28, No. 4 (2005)

Fig. 7 The comparison between cooling load due to solar radia-tion of specified glass window calculated from SCL val-ues from ASHRAE and ones calculated from SCL valuesbased on 2nd weather data set

ASHRAE American Society of Heating, Refriger-ating and Air Conditioning Engineers

CLF internal cooling load factorsCLTD cooling load temperature differencesd time delayDr mean daily rangei indexqt hourly heat gain at time t, Wqmax maximum heat gain of magnitude 1 wattQ cooling load, WSC shading coefficientSCL solar cooling load factors, W/m2

Td maximum dry bulb temperature, °CTo hourly dry bulb temperature, °CTFM transfer function methodU overall head transfer coefficient for

surface, W/m2-°CX percentile of daily variation of dry bulb

temperaturevi, wi coefficient of room transfer function or

weighting factorsφ phase lag, radians

REFERENCES

American Society of Heating, Refrigerating and AirConditioning Engineers, 1977, ASHRAE Hand-book of Fundamentals, Atlanta, GA, USA.

American Society of Heating, Refrigerating and Air

Conditioning Engineers, 1997a, ASHRAE Hand-book of Fundamentals, Atlanta, GA, USA, chap-ter 28, pp. 28.1-28.64.

American Society of Heating, Refrigerating and AirConditioning Engineers, 1997b, ASHRAE Hand-book of Fundamentals, Atlanta, GA, USA, chap-ter 26, pp. 26.1-26.4.

Chaiyapinunt, S., and Mangkornsaksit, K., 2000,“Mathematical Models for Hourly Diffuse SolarRadiation at Bangkok,” Journal of Energy, Heatand Mass Transfer, Vol. 22, pp. 1-6.

Kerrisk, J. F., 1981, “Weighting Factors,” DOE2.1 E.Engineering Manual , Lawrence BerkeleyLaboratory, Berkeley, CA, USA, Vol. 1, pp. II.30-II.31.

Mitalas, G. P., 1972, “Transfer Function Method ofCalculating Cooling Loads, Heat Extraction Rate,and Space Temperature,” ASHRAE Journal, Vol.14, No. 12; pp. 52.

Sowell, E. F., 1984, “A Preview of Weighting FactorResults for ASHRAE Project 359-RP UpdatingCooling Load Temperature Differences and Cool-ing Load Factors for Chapter 26, HOF,” FinalReport, Fullerton, CA, USA.

Sowell, E. F., 1988a, “Classification of 200,640 Para-metric Zones for Cooling Load Calculations,”ASHRAE Transaction, Vol. 94, Part 2A, pp. 754-777.

Sowell, E. F., 1988b, “Cross-Check and Modifica-tion of DOE2 Program for Calculation of ZoneWeighting Factor,” ASHRAE Transaction, Vol.94, Part 2A, pp. 737-753.

Sowell, E. F., 1988c, “Load Calculations for 200,640Zones”, ASHRAE Transaction, Vol. 94, Part 2A,pp. 716-736.

Sowell, E. F., and Chiles, D. C., 1985a, “Character-ization of Zone Dynamic Response for CLF/CLTD Tables,” ASHRAE Transaction, Vol.91,Part 2A, pp. 162-178.

Sowell, E. F., and Chiles, D. C., 1985b, “Zone De-scriptions and Response Characterization forCLF/CLTD Calculation,” ASHRAE Transaction,Vol. 91, Part 2A, pp. 179-200.

Takeda, H., 1990/1991, “Tokyo Weather Data for Air-Conditioning Outdoor Design Conditions forHeating and Cooling Loads by TAC Method,”Energy and Building, Vol. 15, pp. 263-269.

Manuscript Received: Apr. 13, 2004Revision Received: Aug. 23, 2004

and Accepted: Sep. 16, 2004

8000

7000

6000

5000

4000

3000

2000

1000

00 2 4 6 8 12

Hour

ASHRAE east solar loadEast solar load 2nd weatherASHRAE west solar loadWest solar load 2nd weather

14 16 18 20 22 21 24

Sola

r ra

diat

ion

load

(W

att)