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Evaluation of existing cooling systems for reducing cooling power consumption
Energy and Buildings 39 (2007) 105–112 www.elsevier.com/locate/enbuild
Evaluation of existing cooling systems for reducing cooling power consumption M.S. Hatamipour a,*, H. Mahiyar b, M. Taheri b a
Chemical Engineering Department, Isfahan University, Isfahan, Iran Chemical Engineering Department, Shiraz University, Shiraz, Iran
b
Received 18 April 2006; received in revised form 12 May 2006; accepted 23 May 2006
Abstract This work was designed to estimate the cooling load power consumption during the summer in the hot and humid areas of Iran. The actual electrical energy consumption for cooling systems of some typical buildings with various applications (3 residential home buildings, 2 industrial plant buildings, a trade center with 38 shops, 3 public sectors and a city hospital) in a hot and humid region in South of Iran was recorded during the peak load period of the year (July–August). The records were used for estimating the total power consumption of the cooling systems in this region. According to this estimation, which was confirmed by the regional electrical power distribution office, the cooling systems power consumption in this region accounted for more than 60% of the total power consumption during the peak load period of the year. A computer program was developed for simulating the effect of various parameters on cooling load of the buildings in hot and humid regions. According to the simulation results, use of double glazed windows, light colored walls and roofs, and insulated walls and roofs can reduce the cooling load of the buildings more than 40%. # 2006 Elsevier B.V. All rights reserved. Keywords: Cooling-load; Energy management; Energy savings; Peak shaving
1. Introduction Iran is located in Southwest Asia and shares border with Turkmenistan, Armenia, Afghanistan, Iraq, Pakistan and Turkey. Iran covers an area of some 1,648,000 km2 and extends between latitudes 258 and 408N and longitudes 448 and 638E. Iran has a complex climate, ranging from subtropical to sub-polar. In the summer, temperatures vary from a high of 50 8C to a low of 1 8C across the country. The northern and north-western parts are cool, the east region is extremely hot and semi-arid, the coastal strip in the south of the country is hot and humid. In the residential sector of the hot and humid region, the use of room air conditioners during the long summer period caused a high and even rising cooling load and electricity consumption, a high peak cooling load and peak electricity demand. For this reason, further power plants are needed every year, which requires larger energy consumption and more rapid energy-resource depletion. This all, however, impacts on the local (SOx, NOx) and global (CO2)
* Corresponding author. E-mail address: [email protected] (M.S. Hatamipour). 0378-7788/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2006.05.007
environment adversely. Furthermore, the specific cultural, social and economical conditions of the warm and humid region, pushed the government to admit some special subsidies on the electrical power invoices of the users, and this caused the construction of low energy-efficient homes and also, use of low energy efficient appliances. According to article 121 of third development program of the Islamic republic of Iran, the optimization of energy consumption was first mandatory for governmental sector buildings, but from 2004 it is extended to all residential sector buildings. It is therefore crucial the efficient use of energy and the promotion of energy saving in designing new residential buildings and renovation of old buildings. Extensive research is recorded in the literature about optimization of energy consumption in buildings. Windows have a significant role with critical responsibility in connecting the indoor environment of building to the outdoor. Buildings with large areas of glazing, incur excessively high electrical demands. One way of reducing the magnitude of this demand is through better window design. It has been shown that use of colored and coated (thermal insulated) glazing [25,44], double or triple layer glazing units [10], smart windows [69], choosing the optimum sized windows [9], windows overhang [65], tinted
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Nomenclature AD AG AR AW D F hj hiR I m NR NW P QRad QL Qs TRi TWi T1i TG TD TRi V˙ Wi Wo
surface area of doors area of glasses of windows area of external roofs surface area of walls diffusive intensity of radiation lighting coefficient (F = 1.2 for fluorescent lamps and 1 for others) heat transfer coefficient heat transfer coefficient of the air under the roof intensity of direct sun radiation mass flow rate of air no. of external roofs no. of external walls power consumption for lighting system rate of heat absorption per surface area of black body latent heat due to air flow sensible heat due to air flow temperature of interior surface of the roof temperature of interior surface of the wall temperature of interior air temperature of glass temperature of doors temperature of the internal surface of the roof volumetric flow rate of air humidity of inlet air humidity of outlet air
Greek symbols a absorption coefficient l latent heat of vaporization r density of air tI transmission coefficient of glass for direct solar radiation tD transmission coefficient of glass for diffuse radiation and reflective glazing and choosing the best orientation of the windows [19] are the ways to reduce cooling load of the building contributed by the windows. Using skytherm and cooled ceiling systems [14,59,60,67], reflective roofs [3,14,63], high-albedo roof ceiling [4,20], green roofs [61,62,66,75] and shaded roofs [45,64], passive cooling of the buildings [13,32–34,41], natural ventilation [1,28,32,73], thermal mass [12,72], solar control of buildings such as shading with plants and proper tree plantation [5,62,66], shading with nearby buildings [45], insulating envelopes and external surfaces of the buildings [17,18,71], sealing of ducts [55] are other effective ways for reducing cooling loads of the buildings. In addition to above mentioned factors, sensor-based demand controlled ventilation [21,22,31,51], heat pump [79] and phase change materials [27,40,42,76], use of renewable energy sources such as solar radiation and wind energy for
driving cooling systems [6,8,15,16,24,29,39,50,53,77], setting the comfort temperature to its higher value [11,23,58], optimum thermal design of buildings [7], reducing lighting units in daytime and using day-lighting [46,48,68,70], using low-energy consuming systems such as absorption chillers [39,52], cooling storage, ice storage and off-peak cooling [2,26,30,35–38,43,47,49,52,54,56,74,78], and improving the standards of household appliances [57] are other important factors that are of great concern in energy management. This paper describes a short-term field study of cooling loads of buildings carried out during a hot summer in 2004 in some buildings with different applicability in Bushehr. The objectives of the work were to use the proven results of the above literature and: - Estimate the cooling load power consumption during the summer in Bushehr. - Taking field records from power consumption of some buildings with different applications and extract the actual cooling power consumption of the province from the results of this survey. - Suggesting some rules for reducing the cooling load power consumption in this province. 2. Climate of Bushehr Bushehr is a hot and humid province located in south of Iran. It is a coastal province located in the north of Persian Gulf at a latitude of 278140 N and extends between longitudes 50860 to 528580 E. Seven months in year, May to November are the hot months in the province, and July–August are the months of harsh condition of heat. Figs. 1 and 2 show the typical daily temperature and relative humidity changes during one year obtained from the meteorological office of Bushehr. During seven months in year, about 150,000 home users, use more than 300,000 room air conditioners (packaged air conditioning units). 3. Calculation of cooling load For sizing the air conditioning system for a building, the cooling load of the building might be calculated [80]. Total cooling load can be calculated by considering into account the
Fig. 1. Temperature history of Bushehr in 2004.
M.S. Hatamipour et al. / Energy and Buildings 39 (2007) 105–112
107
Cooling load due to outside air flow can be calculated by use of Eq. (7). QAirflow ¼ Qs þ QL
(7)
where ˙ p ðT o T i Þ ¼ mc Qs ¼ Vrc ˙ p ðT o T i Þ
(8)
ðsensible heat by entering airÞ ˙ QL ¼ VrðW i W o Þl Fig. 2. Percent relative humidity of Bushehr in 2004.
effect of various parameters according to Eq. (1). QCooling ¼ QTransmission þ QSolar þ QInternal þ QAirflow
(1)
where QCooling is the total cooling load, QTransmission the cooling load due to heat transfer from exterior walls and envelopes, QSolar the cooling load due to sun radiation transmitted from windows, QInternal the cooling load due to heat generated by appliances, persons, etc. and QAirflow is the cooling load due to airflow into the building (sensible and latent heat). For each of above terms some well-known equations are developed and can be used with care. Heat transmitted from exterior walls and envelopes can be found from Eq. (2). QTransmission ¼ hi
NW X
½AW j ðT Wi T 1i Þ j þ AG j ðT G T 1i Þ j
j¼1
þ AD j ðT D T 1i Þ j þ hiR
NR X
AR j ðT Ri T 1i Þ j
j¼1
(2) Wall temperature must be calculated by mathematical modeling of the unsteady state heat transfer in the wall. It depends on radiation intensity, variations of external air temperature and accumulation of heat inside the wall. Rate of heat absorption due to radiation on black bodies can be calculated by Eq. (3). QRad ¼ aðI þ DÞ
(3)
A major part of cooling load of buildings is transmission of sun radiation through windows of buildings. Cooling load due to this phenomenon can be calculated by using Eq. (4). QSolar ¼ t I I þ tD D
(4)
Internal cooling load is mainly due to heat generated by lighting system, persons in the building and home appliances. So, internal cooling load can be calculated by using Eq. (5). QInternal ¼ QLighting þ QPersons þ Qappliances :
(5)
Heat generated by lighting system can be calculated by using Eq. (6). Heat generated by persons and appliances can be found from appropriate tables [80]. QLighting ¼ P F
(6)
ðlatent heat by entering airÞ
(9)
The capacity of air conditioning system must be calculated for maximum cooling load, by a trial and error procedure based on above equations for various times of the days in peak load of the year. V AC ¼
QCooling rCp ðT 1o T AC Þ
(10)
4. Materials and methods According to previous records of the regional electrical power distribution office of Bushehr, the peak load period for electrical power consumption usually occurs in second mid of July and first mid of August. In order to investigate the state of energy consumption during peak load period in Bushehr, nine case studies on energy consumption of buildings were performed. The buildings had been selected from different applications, namely 3 residential buildings, 2 industrial manufacturing plants, a city hospital, 2 governmental office buildings and a commercial trade center with 38 stores. The selected buildings did not use any special technology for energy saving. The annual power consumption of each building was determined by recording the maximum total power consumption of the building during peak load period, and then subtracting from it the power consumption of all non-air conditioning electrical appliances in use in the building. By taking the average power consumption of the buildings with the same applicability, and assuming the same behavior for power consumption of buildings with similar application in the province, the total cooling (air-conditioning) power consumption for the province was estimated. By dividing the cooling power consumption to the total power consumption of the province, the portion of the power used for cooling purpose can be determined. A computer program (named BLC1) was designed for predicting the cooling load of the selected buildings based on above mentioned equations and accompanying tables. The validity of simulation program was confirmed with doing simulation for two cases, namely residential building no. 1 and city hospital (this consistency can be seen in Table 5). These two buildings were selected because of their low chances for heat loss. After the confirmation of simulation results, the program was used for predicting the effects of various parameters on cooling load of the buildings. 1
Building load calculation.
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Table 1 The specifications of the city hospital building
Table 3 Existing electrical appliances in the city hospital
Parameter
Description
Appliance
Shell wall
Hollow concrete blocks (sand and gravel agg.), white cement plaster as exterior finish, thickness = 27 cm, k = 1.6 W/(m 8C), r = 990 kg/m3, solar heat absorption = 0.56 Hollow concrete blocks, thickness = 36 cm, k = l.4 W/(m 8C), solar heat absorption = 0.98 2 cm gypsum plaster, light green color Aluminum frame, 1.6 m 0.8 m Ordinary glass, 4 mm thick Vertical screen, light brown color Tmax = 48 8C, Tmin = 38 8C, Twet bulb = 32 8C 4500 m3/h 30 persons in building Lighting heat load = 15 w/m2 1100 m 2
Roof Interior wall Window Glass type Curtain Air temperature Air rate Persons Lighting Built over area
4.1. Case studies As pointed out above, nine case studies were performed in this project on buildings with different applications. The selected buildings were: 1 2&3 4–6 7&8 9
A city hospital Governmental office buildings no. 1 and 2 Residential buildings no. 1, 2 and 3 Industrial manufacturing plants no. 1 and 2 A commercial trade center
For brevity in this section the procedure and results for two of the selected buildings (city hospital building and governmental office building no. 2) with the summary of results for all buildings is presented. Tables 1 and 2 show the specifications of these buildings along with the parameters used in BLC program. Electrical appliances in the buildings are listed in Tables 3 and 4. The cooling load of each building was first estimated for the base case (present existing conditions), and then by changing the various parameters (in 12 different conditions) the cooling
Number
RAC package 18,000 RAC split type, 24,000 Lighting Gas bulb Fluorescent
Unit power consumption (W)
Total power consumption (kW)
18 2
2500 2900
92.5 5.8
2 312
250 40
0.5 12.48
7 6
400 140
2.8 0.84
PC Refrigerator Total
114.92
RAC: room air conditioner, PC: personal computer.
load was estimated. A comparison between the predicted value by BLC for the present cases and installed cooling systems is given in Table 5. The 13 different conditions used in simulation are listed in Table 6 and the results of simulation are given in Tables 7 and 8.
Table 4 Existing electrical appliances in the governmental building no. 2 Appliance RAC package 18,000 RAC split type, 24,000 RAC split type, 30,000 Lighting Gas bulb Fluorescent Fluorescent PC Refrigerator
Number
Unit power consumption (W)
Total power consumption (kW)
16
2500
40.00
13
2900
20.30
1
4000
4.00
9 110 39
250 40 20
2.23 4.40 0.78
4 3
400 140
1.6 0.42
Total
73.75
RAC: room air conditioner, PC: personal computer. Table 2 The specifications of the governmental building no. 2 Parameter
Description
Shell wall
Hollow concrete blocks (sand and gravel agg.), finished brick as exterior facing, thickness = 27 cm, k = 1.6 W/(m 8C), r = 990 kg/m3, solar heat absorption = 0.56 Hollow concrete blocks, thickness = 36 cm, k = 1.4 W/(m 8C), solar heat absorption = 0.98 2 cm gypsum plaster, light green color Iron frame, 1.5 m 1.5 m Reflex glass, 4 mm thick Vertical screen, light green color Tmax = 48 8C, Tmin = 38 8C, Twet bulb = 32 8C 648 m3/h 30 persons in building Lighting heat load = 15 w/m2 1220 m 2
Roof Interior wall Window Glass type Curtain Air temperature Air rate Persons Lighting Built over area
Table 5 Comparison between installed cooling systems and that predicted by BLC for selected buildings Building
Installed cooling system (kW)
Cooling load predicted by BLC (kW)
Governmental building no. 1 Governmental building no. 2 Commercial trade center
185.7 64.3 130.3
204.0 51.95 –
Industrial plant no. 1 Office Plant site
37.1 147.82
16.9 –
57.5 5.4 5.0 5.0 98.3
– 5.56 5.9 2.99 85.2
Industrial plant no. 2 Residential building no. 1 Residential building no. 2 Residential building no. 3 City hospital
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Table 6 Different cases used in cooling load simulation for city hospital Case
Title
Description
l
Base case
2 3 4
Effect of color of interior curtain Effect of existence of interior curtain Effect of outside shading screen
5
Effect of glass type
6 7 8 9
Effect Effect Effect Effect
Building with ordinary walls and roofs (mild color), ordinary glass, interior curtain (glass factor = 0.05) Like case 1, curtain light color (glass factor = 0.56) Like case 1, without curtain (glass factor = 1.0), Like case 1, with outside shading screen (458 angle, glass factor = 0.15), no interior curtain Like case 4, windows with reflex glass with color coefficient of 50% (glass factor = 0.11) Like case 4, but light color roof (roof absorbance = 0.4, glass factor = 0.15) Like case 6, but light color wall (wall absorbance = 0.4, glass factor = 0.15) Like case 6, but doubled air circulation rate Like case 1, but with double glazed windows (distance between glasses = 1 cm) Like case 8, but light color of exterior walls and roofs
10
of of of of
outside color of roofs color of exterior wall finish air circulation rate double glazed window
12
Effect of combined double glazed windows + color of exterior walls and roofs Effect of combined double glazed windows + color of exterior walls and roofs + outside screen shading Effect of insulating the roof
13
Effect of insulating the shell walls
11
Like case 9, but with external shading screen Like case 10, but with 5 cm sand wool insulate on roof, k = 0.038 W/(m 8C), r = 100 kg/m3 Like case 11, but with 5 cm sand wool insulate in walls
Table 7 Results of simulation of cooling load for city hospital based on cases of Table 6 Case
Sensible cooling load (W)
Latent cooling load (W)
Total cooling load (W)
Peak load cooling consumptiona (kW)
Reduction (%)
1 2 3 4 5 6 7 9 10 11 12 13
120754 110817 130973 106153 104989 101415 100745 109623 104110 91614 85267 79684
70999 70999 70999 70999 70999 70999 70999 70999 70999 70999 70999 70999
191753 189125 201972 177152 175988 172413 171744 180622 175110 162613 156266 150683
85.2 84.0 89.8 78.7 78.2 76.6 76.3 80.3 77.8 72.3 69.5 67.0
– 1.4 5.3 7.6 8.2 10.0 10.4 5.8 8.7 15.2 18.5 21.4
a
Coefficient of performance is considered to be 2.25 for cooling systems.
Table 8 Results of simulation of cooling load for governmental building no. 2 based on cases of Table 6 Case
Sensible cooling load (W)
Latent cooling load (W)
Total cooling load (W)
Peak load cooling consumptiona (kW)
Reduction (%)
1 2 4 5 6 7 8 9 10 11 12 13
107298 106274 102004 101627 95597 93501 98776 98550 90240 87104 78773 58958
9589 9589 9589 9589 9589 9589 17195 9589 9589 9589 9589 9589
116887 115863 111593 111216 105186 103090 115971 108139 99829 96693 88362 68547
51.95 51.49 49.59 49.43 46.75 45.8 51.54 48.06 44.37 42.97 39.27 30.46
– 0.87 4.5 4.9 10 11.8 – 7.5 14.6 17.3 24.4 41.3
a
Coefficient of performance is considered to be 2.25 for cooling systems.
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5. Results and discussion In this paper, two case studies was presented in detail, in addition to results for seven other cases to verify the annual electrical energy savings associated with cooling systems in hot and humid regions. It was found that in most cases the cooling load predicted by BLC for the present conditions of buildings, is less than the installed cooling system. For preventing the continuation of this situation, people must be informed about the advantages of energy saving programs. For residential buildings no. 1 and 2, and city hospital the consistency between the installed cooling systems and the values predicted by BLC were good. In these buildings, the area of glasses was very small. The selected industrial plants had thick walls with no side windows, and both were cooled by use of central air conditioning systems. Therefore, no further savings was possible for these plants. In governmental building no. 1, the installed cooling systems were separate air cooling packages for each room, and the passageways and halls were not cooled at all. Therefore, the estimation of BLC was more than the installed cooling systems. In governmental building no. 2 that was recently constructed, the installed cooling systems were oversized and therefore a smaller value was predicted for this building by BLC. Both of buildings need to use some type of energy saving technology. The commercial trade center was consisted of 38 shops, and each shop used its own air-cooling package, the exhausted heat from the packages was released to passageways, and the passageways were open to outside air freely without any shield or door. The circulation of hot outside air through the passageways, and release of exhausted heat from air conditioning packages, caused an undesirable air for people passing through them. For this building with present conditions BLC cannot predict any saving. For residential building no. 3, the predicted value for cooling load was less than the installed value. The reason is that in this building, a large fan was installed for ventilation of air which caused about 2 kW additional cooling load in the building. The results of investigation revealed that about 61% of the total energy consumption in Bushehr province was used for cooling purposes, and unfortunately, this high value has an increasing trend, and its continuation needs installing more gas turbines for power generation each year. Therefore, it is advisable to consider energy saving options for buildings in this province. It is hoped that the information provided in this paper will assist in developing more effective measurement and verification procedures for energy efficiency programs. 6. Conclusion According to the results of simulation, the following items can be recommended for energy saving in Bushehr:
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Evaluation of existing cooling systems for reducing cooling power consumption M.S. Hatamipour a,*, H. Mahiyar b, M. Taheri b a
Chemical Engineering Department, Isfahan University, Isfahan, Iran Chemical Engineering Department, Shiraz University, Shiraz, Iran
b
Received 18 April 2006; received in revised form 12 May 2006; accepted 23 May 2006
Abstract This work was designed to estimate the cooling load power consumption during the summer in the hot and humid areas of Iran. The actual electrical energy consumption for cooling systems of some typical buildings with various applications (3 residential home buildings, 2 industrial plant buildings, a trade center with 38 shops, 3 public sectors and a city hospital) in a hot and humid region in South of Iran was recorded during the peak load period of the year (July–August). The records were used for estimating the total power consumption of the cooling systems in this region. According to this estimation, which was confirmed by the regional electrical power distribution office, the cooling systems power consumption in this region accounted for more than 60% of the total power consumption during the peak load period of the year. A computer program was developed for simulating the effect of various parameters on cooling load of the buildings in hot and humid regions. According to the simulation results, use of double glazed windows, light colored walls and roofs, and insulated walls and roofs can reduce the cooling load of the buildings more than 40%. # 2006 Elsevier B.V. All rights reserved. Keywords: Cooling-load; Energy management; Energy savings; Peak shaving
1. Introduction Iran is located in Southwest Asia and shares border with Turkmenistan, Armenia, Afghanistan, Iraq, Pakistan and Turkey. Iran covers an area of some 1,648,000 km2 and extends between latitudes 258 and 408N and longitudes 448 and 638E. Iran has a complex climate, ranging from subtropical to sub-polar. In the summer, temperatures vary from a high of 50 8C to a low of 1 8C across the country. The northern and north-western parts are cool, the east region is extremely hot and semi-arid, the coastal strip in the south of the country is hot and humid. In the residential sector of the hot and humid region, the use of room air conditioners during the long summer period caused a high and even rising cooling load and electricity consumption, a high peak cooling load and peak electricity demand. For this reason, further power plants are needed every year, which requires larger energy consumption and more rapid energy-resource depletion. This all, however, impacts on the local (SOx, NOx) and global (CO2)
* Corresponding author. E-mail address: [email protected] (M.S. Hatamipour). 0378-7788/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2006.05.007
environment adversely. Furthermore, the specific cultural, social and economical conditions of the warm and humid region, pushed the government to admit some special subsidies on the electrical power invoices of the users, and this caused the construction of low energy-efficient homes and also, use of low energy efficient appliances. According to article 121 of third development program of the Islamic republic of Iran, the optimization of energy consumption was first mandatory for governmental sector buildings, but from 2004 it is extended to all residential sector buildings. It is therefore crucial the efficient use of energy and the promotion of energy saving in designing new residential buildings and renovation of old buildings. Extensive research is recorded in the literature about optimization of energy consumption in buildings. Windows have a significant role with critical responsibility in connecting the indoor environment of building to the outdoor. Buildings with large areas of glazing, incur excessively high electrical demands. One way of reducing the magnitude of this demand is through better window design. It has been shown that use of colored and coated (thermal insulated) glazing [25,44], double or triple layer glazing units [10], smart windows [69], choosing the optimum sized windows [9], windows overhang [65], tinted
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Nomenclature AD AG AR AW D F hj hiR I m NR NW P QRad QL Qs TRi TWi T1i TG TD TRi V˙ Wi Wo
surface area of doors area of glasses of windows area of external roofs surface area of walls diffusive intensity of radiation lighting coefficient (F = 1.2 for fluorescent lamps and 1 for others) heat transfer coefficient heat transfer coefficient of the air under the roof intensity of direct sun radiation mass flow rate of air no. of external roofs no. of external walls power consumption for lighting system rate of heat absorption per surface area of black body latent heat due to air flow sensible heat due to air flow temperature of interior surface of the roof temperature of interior surface of the wall temperature of interior air temperature of glass temperature of doors temperature of the internal surface of the roof volumetric flow rate of air humidity of inlet air humidity of outlet air
Greek symbols a absorption coefficient l latent heat of vaporization r density of air tI transmission coefficient of glass for direct solar radiation tD transmission coefficient of glass for diffuse radiation and reflective glazing and choosing the best orientation of the windows [19] are the ways to reduce cooling load of the building contributed by the windows. Using skytherm and cooled ceiling systems [14,59,60,67], reflective roofs [3,14,63], high-albedo roof ceiling [4,20], green roofs [61,62,66,75] and shaded roofs [45,64], passive cooling of the buildings [13,32–34,41], natural ventilation [1,28,32,73], thermal mass [12,72], solar control of buildings such as shading with plants and proper tree plantation [5,62,66], shading with nearby buildings [45], insulating envelopes and external surfaces of the buildings [17,18,71], sealing of ducts [55] are other effective ways for reducing cooling loads of the buildings. In addition to above mentioned factors, sensor-based demand controlled ventilation [21,22,31,51], heat pump [79] and phase change materials [27,40,42,76], use of renewable energy sources such as solar radiation and wind energy for
driving cooling systems [6,8,15,16,24,29,39,50,53,77], setting the comfort temperature to its higher value [11,23,58], optimum thermal design of buildings [7], reducing lighting units in daytime and using day-lighting [46,48,68,70], using low-energy consuming systems such as absorption chillers [39,52], cooling storage, ice storage and off-peak cooling [2,26,30,35–38,43,47,49,52,54,56,74,78], and improving the standards of household appliances [57] are other important factors that are of great concern in energy management. This paper describes a short-term field study of cooling loads of buildings carried out during a hot summer in 2004 in some buildings with different applicability in Bushehr. The objectives of the work were to use the proven results of the above literature and: - Estimate the cooling load power consumption during the summer in Bushehr. - Taking field records from power consumption of some buildings with different applications and extract the actual cooling power consumption of the province from the results of this survey. - Suggesting some rules for reducing the cooling load power consumption in this province. 2. Climate of Bushehr Bushehr is a hot and humid province located in south of Iran. It is a coastal province located in the north of Persian Gulf at a latitude of 278140 N and extends between longitudes 50860 to 528580 E. Seven months in year, May to November are the hot months in the province, and July–August are the months of harsh condition of heat. Figs. 1 and 2 show the typical daily temperature and relative humidity changes during one year obtained from the meteorological office of Bushehr. During seven months in year, about 150,000 home users, use more than 300,000 room air conditioners (packaged air conditioning units). 3. Calculation of cooling load For sizing the air conditioning system for a building, the cooling load of the building might be calculated [80]. Total cooling load can be calculated by considering into account the
Fig. 1. Temperature history of Bushehr in 2004.
M.S. Hatamipour et al. / Energy and Buildings 39 (2007) 105–112
107
Cooling load due to outside air flow can be calculated by use of Eq. (7). QAirflow ¼ Qs þ QL
(7)
where ˙ p ðT o T i Þ ¼ mc Qs ¼ Vrc ˙ p ðT o T i Þ
(8)
ðsensible heat by entering airÞ ˙ QL ¼ VrðW i W o Þl Fig. 2. Percent relative humidity of Bushehr in 2004.
effect of various parameters according to Eq. (1). QCooling ¼ QTransmission þ QSolar þ QInternal þ QAirflow
(1)
where QCooling is the total cooling load, QTransmission the cooling load due to heat transfer from exterior walls and envelopes, QSolar the cooling load due to sun radiation transmitted from windows, QInternal the cooling load due to heat generated by appliances, persons, etc. and QAirflow is the cooling load due to airflow into the building (sensible and latent heat). For each of above terms some well-known equations are developed and can be used with care. Heat transmitted from exterior walls and envelopes can be found from Eq. (2). QTransmission ¼ hi
NW X
½AW j ðT Wi T 1i Þ j þ AG j ðT G T 1i Þ j
j¼1
þ AD j ðT D T 1i Þ j þ hiR
NR X
AR j ðT Ri T 1i Þ j
j¼1
(2) Wall temperature must be calculated by mathematical modeling of the unsteady state heat transfer in the wall. It depends on radiation intensity, variations of external air temperature and accumulation of heat inside the wall. Rate of heat absorption due to radiation on black bodies can be calculated by Eq. (3). QRad ¼ aðI þ DÞ
(3)
A major part of cooling load of buildings is transmission of sun radiation through windows of buildings. Cooling load due to this phenomenon can be calculated by using Eq. (4). QSolar ¼ t I I þ tD D
(4)
Internal cooling load is mainly due to heat generated by lighting system, persons in the building and home appliances. So, internal cooling load can be calculated by using Eq. (5). QInternal ¼ QLighting þ QPersons þ Qappliances :
(5)
Heat generated by lighting system can be calculated by using Eq. (6). Heat generated by persons and appliances can be found from appropriate tables [80]. QLighting ¼ P F
(6)
ðlatent heat by entering airÞ
(9)
The capacity of air conditioning system must be calculated for maximum cooling load, by a trial and error procedure based on above equations for various times of the days in peak load of the year. V AC ¼
QCooling rCp ðT 1o T AC Þ
(10)
4. Materials and methods According to previous records of the regional electrical power distribution office of Bushehr, the peak load period for electrical power consumption usually occurs in second mid of July and first mid of August. In order to investigate the state of energy consumption during peak load period in Bushehr, nine case studies on energy consumption of buildings were performed. The buildings had been selected from different applications, namely 3 residential buildings, 2 industrial manufacturing plants, a city hospital, 2 governmental office buildings and a commercial trade center with 38 stores. The selected buildings did not use any special technology for energy saving. The annual power consumption of each building was determined by recording the maximum total power consumption of the building during peak load period, and then subtracting from it the power consumption of all non-air conditioning electrical appliances in use in the building. By taking the average power consumption of the buildings with the same applicability, and assuming the same behavior for power consumption of buildings with similar application in the province, the total cooling (air-conditioning) power consumption for the province was estimated. By dividing the cooling power consumption to the total power consumption of the province, the portion of the power used for cooling purpose can be determined. A computer program (named BLC1) was designed for predicting the cooling load of the selected buildings based on above mentioned equations and accompanying tables. The validity of simulation program was confirmed with doing simulation for two cases, namely residential building no. 1 and city hospital (this consistency can be seen in Table 5). These two buildings were selected because of their low chances for heat loss. After the confirmation of simulation results, the program was used for predicting the effects of various parameters on cooling load of the buildings. 1
Building load calculation.
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Table 1 The specifications of the city hospital building
Table 3 Existing electrical appliances in the city hospital
Parameter
Description
Appliance
Shell wall
Hollow concrete blocks (sand and gravel agg.), white cement plaster as exterior finish, thickness = 27 cm, k = 1.6 W/(m 8C), r = 990 kg/m3, solar heat absorption = 0.56 Hollow concrete blocks, thickness = 36 cm, k = l.4 W/(m 8C), solar heat absorption = 0.98 2 cm gypsum plaster, light green color Aluminum frame, 1.6 m 0.8 m Ordinary glass, 4 mm thick Vertical screen, light brown color Tmax = 48 8C, Tmin = 38 8C, Twet bulb = 32 8C 4500 m3/h 30 persons in building Lighting heat load = 15 w/m2 1100 m 2
Roof Interior wall Window Glass type Curtain Air temperature Air rate Persons Lighting Built over area
4.1. Case studies As pointed out above, nine case studies were performed in this project on buildings with different applications. The selected buildings were: 1 2&3 4–6 7&8 9
A city hospital Governmental office buildings no. 1 and 2 Residential buildings no. 1, 2 and 3 Industrial manufacturing plants no. 1 and 2 A commercial trade center
For brevity in this section the procedure and results for two of the selected buildings (city hospital building and governmental office building no. 2) with the summary of results for all buildings is presented. Tables 1 and 2 show the specifications of these buildings along with the parameters used in BLC program. Electrical appliances in the buildings are listed in Tables 3 and 4. The cooling load of each building was first estimated for the base case (present existing conditions), and then by changing the various parameters (in 12 different conditions) the cooling
Number
RAC package 18,000 RAC split type, 24,000 Lighting Gas bulb Fluorescent
Unit power consumption (W)
Total power consumption (kW)
18 2
2500 2900
92.5 5.8
2 312
250 40
0.5 12.48
7 6
400 140
2.8 0.84
PC Refrigerator Total
114.92
RAC: room air conditioner, PC: personal computer.
load was estimated. A comparison between the predicted value by BLC for the present cases and installed cooling systems is given in Table 5. The 13 different conditions used in simulation are listed in Table 6 and the results of simulation are given in Tables 7 and 8.
Table 4 Existing electrical appliances in the governmental building no. 2 Appliance RAC package 18,000 RAC split type, 24,000 RAC split type, 30,000 Lighting Gas bulb Fluorescent Fluorescent PC Refrigerator
Number
Unit power consumption (W)
Total power consumption (kW)
16
2500
40.00
13
2900
20.30
1
4000
4.00
9 110 39
250 40 20
2.23 4.40 0.78
4 3
400 140
1.6 0.42
Total
73.75
RAC: room air conditioner, PC: personal computer. Table 2 The specifications of the governmental building no. 2 Parameter
Description
Shell wall
Hollow concrete blocks (sand and gravel agg.), finished brick as exterior facing, thickness = 27 cm, k = 1.6 W/(m 8C), r = 990 kg/m3, solar heat absorption = 0.56 Hollow concrete blocks, thickness = 36 cm, k = 1.4 W/(m 8C), solar heat absorption = 0.98 2 cm gypsum plaster, light green color Iron frame, 1.5 m 1.5 m Reflex glass, 4 mm thick Vertical screen, light green color Tmax = 48 8C, Tmin = 38 8C, Twet bulb = 32 8C 648 m3/h 30 persons in building Lighting heat load = 15 w/m2 1220 m 2
Roof Interior wall Window Glass type Curtain Air temperature Air rate Persons Lighting Built over area
Table 5 Comparison between installed cooling systems and that predicted by BLC for selected buildings Building
Installed cooling system (kW)
Cooling load predicted by BLC (kW)
Governmental building no. 1 Governmental building no. 2 Commercial trade center
185.7 64.3 130.3
204.0 51.95 –
Industrial plant no. 1 Office Plant site
37.1 147.82
16.9 –
57.5 5.4 5.0 5.0 98.3
– 5.56 5.9 2.99 85.2
Industrial plant no. 2 Residential building no. 1 Residential building no. 2 Residential building no. 3 City hospital
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Table 6 Different cases used in cooling load simulation for city hospital Case
Title
Description
l
Base case
2 3 4
Effect of color of interior curtain Effect of existence of interior curtain Effect of outside shading screen
5
Effect of glass type
6 7 8 9
Effect Effect Effect Effect
Building with ordinary walls and roofs (mild color), ordinary glass, interior curtain (glass factor = 0.05) Like case 1, curtain light color (glass factor = 0.56) Like case 1, without curtain (glass factor = 1.0), Like case 1, with outside shading screen (458 angle, glass factor = 0.15), no interior curtain Like case 4, windows with reflex glass with color coefficient of 50% (glass factor = 0.11) Like case 4, but light color roof (roof absorbance = 0.4, glass factor = 0.15) Like case 6, but light color wall (wall absorbance = 0.4, glass factor = 0.15) Like case 6, but doubled air circulation rate Like case 1, but with double glazed windows (distance between glasses = 1 cm) Like case 8, but light color of exterior walls and roofs
10
of of of of
outside color of roofs color of exterior wall finish air circulation rate double glazed window
12
Effect of combined double glazed windows + color of exterior walls and roofs Effect of combined double glazed windows + color of exterior walls and roofs + outside screen shading Effect of insulating the roof
13
Effect of insulating the shell walls
11
Like case 9, but with external shading screen Like case 10, but with 5 cm sand wool insulate on roof, k = 0.038 W/(m 8C), r = 100 kg/m3 Like case 11, but with 5 cm sand wool insulate in walls
Table 7 Results of simulation of cooling load for city hospital based on cases of Table 6 Case
Sensible cooling load (W)
Latent cooling load (W)
Total cooling load (W)
Peak load cooling consumptiona (kW)
Reduction (%)
1 2 3 4 5 6 7 9 10 11 12 13
120754 110817 130973 106153 104989 101415 100745 109623 104110 91614 85267 79684
70999 70999 70999 70999 70999 70999 70999 70999 70999 70999 70999 70999
191753 189125 201972 177152 175988 172413 171744 180622 175110 162613 156266 150683
85.2 84.0 89.8 78.7 78.2 76.6 76.3 80.3 77.8 72.3 69.5 67.0
– 1.4 5.3 7.6 8.2 10.0 10.4 5.8 8.7 15.2 18.5 21.4
a
Coefficient of performance is considered to be 2.25 for cooling systems.
Table 8 Results of simulation of cooling load for governmental building no. 2 based on cases of Table 6 Case
Sensible cooling load (W)
Latent cooling load (W)
Total cooling load (W)
Peak load cooling consumptiona (kW)
Reduction (%)
1 2 4 5 6 7 8 9 10 11 12 13
107298 106274 102004 101627 95597 93501 98776 98550 90240 87104 78773 58958
9589 9589 9589 9589 9589 9589 17195 9589 9589 9589 9589 9589
116887 115863 111593 111216 105186 103090 115971 108139 99829 96693 88362 68547
51.95 51.49 49.59 49.43 46.75 45.8 51.54 48.06 44.37 42.97 39.27 30.46
– 0.87 4.5 4.9 10 11.8 – 7.5 14.6 17.3 24.4 41.3
a
Coefficient of performance is considered to be 2.25 for cooling systems.
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5. Results and discussion In this paper, two case studies was presented in detail, in addition to results for seven other cases to verify the annual electrical energy savings associated with cooling systems in hot and humid regions. It was found that in most cases the cooling load predicted by BLC for the present conditions of buildings, is less than the installed cooling system. For preventing the continuation of this situation, people must be informed about the advantages of energy saving programs. For residential buildings no. 1 and 2, and city hospital the consistency between the installed cooling systems and the values predicted by BLC were good. In these buildings, the area of glasses was very small. The selected industrial plants had thick walls with no side windows, and both were cooled by use of central air conditioning systems. Therefore, no further savings was possible for these plants. In governmental building no. 1, the installed cooling systems were separate air cooling packages for each room, and the passageways and halls were not cooled at all. Therefore, the estimation of BLC was more than the installed cooling systems. In governmental building no. 2 that was recently constructed, the installed cooling systems were oversized and therefore a smaller value was predicted for this building by BLC. Both of buildings need to use some type of energy saving technology. The commercial trade center was consisted of 38 shops, and each shop used its own air-cooling package, the exhausted heat from the packages was released to passageways, and the passageways were open to outside air freely without any shield or door. The circulation of hot outside air through the passageways, and release of exhausted heat from air conditioning packages, caused an undesirable air for people passing through them. For this building with present conditions BLC cannot predict any saving. For residential building no. 3, the predicted value for cooling load was less than the installed value. The reason is that in this building, a large fan was installed for ventilation of air which caused about 2 kW additional cooling load in the building. The results of investigation revealed that about 61% of the total energy consumption in Bushehr province was used for cooling purposes, and unfortunately, this high value has an increasing trend, and its continuation needs installing more gas turbines for power generation each year. Therefore, it is advisable to consider energy saving options for buildings in this province. It is hoped that the information provided in this paper will assist in developing more effective measurement and verification procedures for energy efficiency programs. 6. Conclusion According to the results of simulation, the following items can be recommended for energy saving in Bushehr:
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