沙漠研究 19-1, 101- 104 (2009 )Journal of Arid Land Studies“Desert Technology IX ”
Refereed Paper

Computation of Space Heating Energy Requirements and Comparative Analysis ofThree Cold Desert Region of Jammu and Kashmir (India)-A Case Study for Solar System DesignsHilal A. BHAT1, Seemin RUBAB1, S.H. BALKHI2, 3, Sanjay KUMAR3, 4*
Abstract: The aim of this study is to determine and present heating degree days for threelocations in Jammu and Kashmir province of India for solar system designs. The heatingenergy requirement of a typical residential building of floor area ~100 m2 in Jammu andKashmir, has been determined and the heating degree days have been calculated for various
base temperatures and are presented in tabular form. The numerical results show that the heatloss from a typical structure in the state is in huge quantity and that can be a significantly
reduced in the heating load using well fitted doors and windows.
Keywords: Heating degree days, Heating load, Space heating energy, Variable base temperature

1. Introduction
The aim of this study is to determine and present heating degree days for three arid and desert
locations in Jammu and Kashmir province of India for solar system designs. Jammu and Kashmir state
constitutes the northern most extremity of India comprising Jammu, Kashmir and Ladakh. The total areaof the province is 222236 km2 of which 19% is under Jammu region, 11% of Kashmir and 70% of Ladakh.
The three regions have distinct climate and topography. Jammu has 26293 km2 of total area. It is situatedbetween the outer hills and has mostly sub-tropical climate. Temperature sometimes touches 45 ˚C. Thereare no snowfalls and the lowest temperature seldom reaches 0 ˚C. The valley of Kashmir is situatedamong the outskirts of the Himalayas in the Pir-Panjal range. Its area is 15948 km2. The topography ofKashmir valley can be classified into three terrains-mountainous, sub-mountainous and plain. Theclimate of three terrains varies from moderate summer to severe winter. The valley of Kashmir has
temperate climate. The summer lasts only a couple of months generally from June to August. During
winters the valley experiences heavy and frequent snowfalls and total average rainfall in the region is~1000 mm. Ladakh region experiences extreme weather condition with temperature dipping to – 40 ˚C.
However, the whole region receives average daily solar radiation of 5-7 kWh/day and there are about 300
clear sunny days per year (Mani and Rangarajan, 1982).
In the present study, heating degree-days have been calculated for three locations in Jammu andKashmir State namely Jammu, Srinagar and Pahalgam. Due to non availability of temperature data ofLadakh region, it has not been considered in this study. Srinagar is the summer capital of Jammu andKashmir. Pahalgam is the famous tourist resort and is the coldest place in the valley of Kashmir. Thedaily ambient temperature data since 2003 has been used to determine heating degree-days for the threelocations under study. Computations indicate that there is tremendous opportunity to use solar energy forspace heating.
2. Degree-Day method
The calculations of seasonal energy consumption are of vital importance in any building design forheating or cooling purposes. In literature several methods are available to estimate energy requirementsof buildings (Marx and Stamber, 1995). There are some computer simulation models which simulate thehourly envelope dynamic heat transfer process as well as the dynamic behaviour of the heating system andequipment. These models are based on thermodynamic principles which are solved numerically using
initial and boundary conditions and also the architectural geometry of the usable spaces of a building.
These models are not practically realistic as they require certain assumptions because of unpredictable
1Department of Physics, National Institute of Technology, Srinagar, Kashmir-190006, India
Project Coordinator, P.O. Box – 809, GPO – Srinagar, Kashmir, Jammu and Kashmir, India
3CREER, PO Box - 5, Muzaffarpur - 842001, Bihar, India; Ph. - +91-9431239820, E-mail: creer@sancharnet.in
4*Chandragupt Institute of Management, Chajubagh, Patna-800001, Bihar, India; Ph. - +91-9431239820,
E-mail: creer@sancharnet.in2

102

Table 1. Geographical details of locations under study.
nature of weather conditions.
StationType ofLatitude
Longitude
Altitude
These methods are known as
nameclimate(˚N)(˚N)
AMSL(m)dynamic methods and require hourly
data for simulation. Some simpler
SrinagarTemperate
34.05
74.50
1588
PahalgamTemperate
32.0
75.20
2310
steady state methods are also
Jammu
Sub-tropical
32.40
74.50
356
available which require less data but
provide lesser degree of information.
Degree day or degree hour method is developed for this area to estimate heating and/or cooling load ofbuildings. The methodology is less data intensive than dynamic methods and more accurate than steadystate methods. During heating season, windows of buildings are usually closed and the air exchange rateis fairly constant. Thus there is not a significant difference among the results using degree day and degreehour method as shown by Papakostas and Kyriakis (2005). The degree day method has been used by afew researchers to estimate the monthly and annual heating and cooling energy requirements of specificbuildings in different climatic conditions. Traditionally, degree days are calculated based on a basetemperature of 18.3 ˚C for a typical none insulated building (Martinatis, 1998).
The daily ambient temperature data since 2003 has been used for determining heating degree-days forthe three locations under study. These data were taken from India Meteorology Department, Rambagh,Srinagar. The geographical detail of locations under study is shown in Table 1. The monthly maximum
and minimum dry bulb temperatures were computed using the recorded daily weather data Table 2. Thebase temperature is not necessarily constant and differs because of various factors like increased insulationlevels, a reduction in set point temperature or large solar gains etc. the heating degree days are therefore
calculated for various base temperatures. The buildings in Jammu and Kashmir state are observed to benon insulated. The heating load is determined based on a base temperature of 18.3 ˚C, however thevariable base degree days can be used for all types of houses using proper insulation and with all types oftheir usage. The monthly heating degree days (HDD) can be expressed as,
HDD=Σ(Tb–Tav) daily(1)where, Tb is base temperature (˚C) and Tav is the average temperature of the day.

2.1. Heating Load
The physical characteristics of building parameters of a typical residential building in the Jammu andKashmir is shown in Table 3 (Sharma, 1984). The total heat loss coefficient of the building is expressedas,
Lh = ΣUA+N (ρCp) air V/3.6 = ΣUA+N V/3(2)where, A is area, N is air exchange rates per hour or air changes per hour (1/h), Lh is heat loss coefficient(W/0C), U is thermal transmittance (W/m2 0C), V is volume of air (m3), ρ is density (kg/ m3), (ρCp)air isvolumetric thermal capacity of air and its numerical value is 1.2 kJ/ m3 0C and Cp is specific heat atconstant pressure (kJ/ kg0C). The monthly heating energy requirement for the building in terms of numberof hours in a day (Nh) can be expressed as,
Q (J) = 3600NhLh (HDD) = 86400Lh (HDD)(3)
3. Results and Discussion
The heating degree day for a location depends upon the severity of the climatic conditions at thatplace. Table 4 shows that Srinagar and Pahalgam has heating degree days in all month except
Table 2. Monthly max (1) and min (2) DBT temp (oC) of three locations under study.

StationSrinagarPahalgam
Jammu

Jan
6.3
-0.4
3.4
-5
18.2
8Feb
10.9
1.7
7.4
-2.2
22.6
11.5

Mar
17.4
5.2
13.6
1.4
2815.6

Apr
20.8
7.6
17.6
3.3
33.9
20.9

May
25.3
11.3
21.8
6.3
38.0
25.3

Jun
28.2
14.7
23.7
9.2
38.6
26.4

Jul
29.7
18.0
25.2
13.1
34.4
25.2

Aug
29.4
17.4
25.1
13.1
33.3
24.6

Sep
28.0
12.8
24.3
9.0
32.6
23.6

Oct
22.0
10.0
18.8
3.3
30.7
18.7

Nov
15.9
1.4
13.2
-1.0
26.3
13.1

Dec
9.5
-1.3
7.1
-4.1
21.1
8.7

103

Physical characteristics of building
parameters and heat loss coefficient.
Heat loss
U-factorfactorDescription
Area (m2)2W/m ˚C(W/ ˚C)
Walls
69.50
2.32
161.24
Ceiling
71.11
2.34
166.46
Windows
13.67
4.86
66.42
Doors
11.46
3.76
43.12
Perimeter
1.29
Floor
49.98
38.51mW/m 0C
Infiltration
Vol. of air
0.33
115.48loss*
173.39m3
W/m3 0C
Total heat----602.7
loss Coeff.

3.

35
Heating energy Q(GJ)

4. Conclusion
The calculation results show that the heatloss in a small residential building is enormous.
A number of steps can be taken to reduce theheating load in pre-existing buildings. The walland roof insulation should be incorporated in thebuildings. Efforts should be put forth to classify
the better insulating envelope in different climaticconditions of the state. In order to maximize
benefits from solar radiation, buildings should bedesigned using passive solar heating techniques.
The site specific Energy Conservation Building
Codes should be developed and these building
codes need to be enforced to motivate theimplementation of energy conscious building
design.

Table

Srinagar

30

Jammu

25

Pahalgam

20
15
1050
SepOctNov

DecJanFebMarAprMay

Heating months

Fig. 1. Energy consumption for Space Heating vs. heating
months in a typical Residential building.
Seasonal heating energy Q(GJ)

July-August. Space heating is the major energy
consuming end-use in the household sector ofKashmir valley. In Jammu region space heating
is required only for three months November,
December and January, the heating degree daysin the rest of months is zero. The energy
consumption for space heating in a typicalresidential building of state (floor area ~ 100 m2)
has been calculated using Eq. 3. Figure 1
shows the energy consumption for space heatingin three different climatic conditions.
Themaximum space heating requirement is in themonth of January (25 GJ).
The present
buildings have poor insulation levels and loosely
fitted doors and windows, so the infiltration load
has been calculated using two air changes perhour Figure 2 shows the variation of heating loadof a building with different air exchange rates,
there can be a significant reduction in the heatingload by using well fitted doors and windows.

180
Srinagar

160

Jammu

140

Pahalgam

120
100
80
60
40
20000.5

11.5

22.5

Air changes per hourReferences

Fig. 2. Seasonal Energy Requirement vs. Air exchange

Mani A., Rangarajan S. (1982): Solar Radiation over India,
rate for a typical Residential building.
N.Delhi, India. Allied Publishers Private Ltd, N. Delhi,
India.
Martinatis V. (1998): Analytical calculation of degree days for the regulated heating season. Energy and Building, 28:185-189.
Marx Ayres J., Stamber E. (1995): Historical development of building energy calculations. ASHRAE, 37(2):47-53.
Papakostas K., Kyriakis N. (2005): Heating and cooling degree hours for Athens and Thessaloniki Greece. Renewable Energy, 30:
1873-1880.
Sharma S.K. (1984): Passive Heating System Design for a Family Residence in Srinagar. NSEC, Bhopal.

Pahalgam

Jammu

Srinagar

Station338.6

330.0

72.8

56.8

51.1

32.1

18

485.7

466.1

457.7

18.3 475.9

466.6

435.6

404.6

373.6

155.5

120.8

90.1

59.5

607.6

545.6

514.6

483.1

1615

19

18

17

16

15

19

18.3 585.9

576.6

1718.3 160.7

151.5

1818

17

16

15

373.5

401.7

429.7

8.9

245.2

273.5

301.8

358.3

502.6

19FebJan

Tb

0000230.7261.2

291.7

322.2

331.3

137.6

167.6

197.6

227.6

236.6

257.6

00

352.7

000

31.2

61.2

91.2

121.2

130.2

151.2

Apr

000

112.7

143.7

174.7

205.7

215.0

236.7

Mar

65.3

96.3

127.3

158.3

167.6

189.3

0

0

0

00

00

1.5

11.9

22.2

32.1

50.6

May

00

16.6

46.6

55.6

76.6

000

0

0

00

0

0

00

9.9

Jun

0

0000

8.7

000000000000Jul

000001.5000000000000Aug

00

8.4

33.542.5

63.5

00

0

0

000000

3.4

11.9

Sep

132.2

162.7

193.2

223.7

232.9

254.2

000000

22.7

48.6

79.2

109.9

119.1

140.6

Oct

Table 4. HDD for various base temperatures for Srinagar, Jammu and Pahalgam.

263.3

293.3

323.3

353.3

362.3

383.3

00

0

0

00

177.8

207.8

237.8

267.8

284.2

304.8

Nov

410.1

441.1

472.1

503.1

512.4

534.1

6.6

29.9

60.2

90.5

99.6

120.9

339.0

370.0

401.0

432.0

441.3

463.0

Dec

2095.82338.52605.52902.62993.23214.8

75.0

138.0

213.1

293.1

317.1

349.2

1302.51511.21733.5

1955.72040.22229.6

Annual104