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The Comprehensive Evaluation of Optimization Air-Condition System Based on Analytic Hierarchy Methodology
Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 105 (2017) 2095 – 2100
The 8th International Conference on Applied Energy – ICAE2016
The Comprehensive Evaluation of Optimization AirCondition System Based on Analytic Hierarchy Methodology Luo Chaoa,b,c,d*, Lu Zhennenga,b,c, Gong Yuliea,b,c , Ma Zhitonga,b,c a
Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China b Key Laboratory of Renewable Energy, Chinese Academy of Science, Guangzhou 510640, China c Guangdong Key Laboratory of New and Renewable Energy Research and Development, Guangzhou 510640, China d Key Laboratory of Efficient Utilization of Low and Medium Grade Energy (Tianjin University), Ministry of Education, Tianjin 300072, China
Abstract The paper presents different kinds of optimization scheme of air-condition system based on equipment technologies and variable parameters in Guangzhou. Coefficients of performance (COP) and energy efficiency of rate (EER) are the main index of air-condition system. The results show that the percentage of optimized air-condition systems are of different weight ratio based on analytic hierarchy process method. Pump and compressor frequency conversion technologies and higher indoor temperature are the main energy efficiency measurements for air-condition system. The results provide a new methodology for evaluating the air conditioning system construction. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
© 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection peer-review of under responsibility of ICAE Peer-reviewand/or under responsibility the scientific committee of the 8th International Conference on Applied Energy. Keywords: air condition system; office building; Analytic Hierarchy Process (AHP); energy-saving potential; optimized design
1. Introduction Air-condition energy consumption accounts for 30% -60% of building energy consumption based on testing of hotel and supermarket in Beijing [1-2]. The building energy consumption includes the envelope heat losses; air-condition electricity consumption and lighting energy consumption. The energy saving potential of air-condition system is evaluated by testing and numerical calculation in China [3-4]. However, there are some problems of air-condition system, such as unreasonable design system, low efficiency of COP and irregular management [5-6].
* Corresponding author. Tel.:+086-020-87058428; fax: +086-020-87057791. E-mail address: [email protected].
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. doi:10.1016/j.egypro.2017.03.589
2096
Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
The paper presents seven optimized air-condition systems, and the economic and energy efficiency of the optimized systems are compared. The factors weights are calculated based on Analytic Hierarchy Process (AHP). 2. Optimized design and energy potential analysis of air-condition system The office building is built in the south of China. The width, length and height of the building are 10 meters, 30 meters and 9 meters. Figure 1 shows the physical model of the building. The first and second floor is supplied chilled air by unit-conditioner, and the third floor is supplied chilled air by central airconditioner. N
Fig. 1. Building physical model
The central air-condition system includes heat/cooled source, water and air transfer system and terminal equipment. In original central air-condition system, the indoor temperature is 26ć, supply air temperature difference between supply air and return air is 7 ć, cold water temperature difference between inlet and outlet is 5ć, cooling water temperature difference between inlet and outlet is 5ć. Table 1 shows the basic data of original central air-condition system. Table 1. Basic data of original central air-condition system Rated cooling capacity (Kw) 50
Parasitic work power (kW) 27.64
CO2 emission per kWh (kg/kWh) 0.8908
Electricity price per kWh (RMB/kWh) 0.65
Operation hours per year (h) 1440
Seven optimal central air-condition schemes are designed from the view of easing operability principles. The measurements include equipment technologies and parameters adjustment. The first optimized scheme is to increase chilled water temperature difference to 10 ć by pump frequency conversion technologies. The second optimized scheme is to increase supplied air temperature difference to 9.8ć by compressor frequency conversion technologies. The third optimized scheme is to set up indoor temperature to 27ć by enhancing the people awareness of energy conservation. The forth optimized scheme is combination of the first scheme and the second scheme. That is to increase chilled water and supplied air temperature difference to 10ć and 9.8ć by pump and compressor frequency conversion technologies. The fifth optimized scheme is combination of the second scheme and the third scheme. That is to increase supplied air temperature difference and set up indoor temperature to 9.8 ć and 27 ć by compressor frequency conversion technologies and enhancing awareness of energy conservation.
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Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
The sixth optimized scheme is combination of the first scheme and the second scheme. That is to increase chilled temperature difference and set up indoor temperature to 10 ć and 27ć by pump frequency conversion technologies and enhancing awareness of energy conservation. The seventh optimized scheme is combination of the first scheme, the second scheme and third scheme. That is to increase chilled, air supplied temperature difference and set up indoor temperature to 10ć, 9.8ć and 27ć by pump, compressor frequency conversion technologies and enhancing awareness of energy conservation. Figure 2 gives the topology diagram of seven optimized schemes. Energy saving technologies
Energy saving technologies of transfer system
Energy saving technologies of heat and chilled source
Optimized scheme II O
Optimized scheme I
Optimized scheme IV
Enhancing awareness of energy conservation
Optimized scheme III
Optimized scheme V
Optimized scheme I
Optimized scheme VI
Optimized scheme VII
Fig. 2. Topology diagram of seven optimized schemes
The performance indexes of central air-condition is calculated by Matlab software. Table 2 gives performance indexes of seven optimized schemes. The five performance indexes are coefficient of performance (COP), energy efficiency ratio (EER), water transfer factor of chilled water ( WTFchilled,water), water transfer factor of cooling water (WTFcooling,water) and indoor temperature. Table 2. Performance indexes of seven optimized schemes Optimized scheme Original system Optimized scheme I Optimized scheme II Optimized scheme III Optimized scheme IV Optimized scheme V Optimized scheme VI Optimized scheme VII
COP 4.105 4.114 3.448 4.382 3.455 3.667 4.392 3.676
EER 3.264 3.356 2.743 3.386 2.283 2.858 3.512 2.961
WTFchilled,water 30.4 43 26.46 29.16 37.42 25.5 41.25 36.06
WTFcooling,water 36.9 36.9 32.44 35.32 32.44 31.6 35.32 31.16
Indoor temperature (ć) 26 26 26 27 26 27 27 27
The energy saving potential comparisons between original and optimized systems is calculated. Table 3 shows the economics, electricity consumption and CO2 emission reduction of different systems. Scheme VII is the best optimized scheme, which can save electricity of 9200 kWh, operation cost of 5900 Yuan and CO2 emission 8.13 t per year. Table 3. Energy saving potential comparisons between original and optimized systems Operating costs
Electricity consumption
CO2 emission
Economics
Electricity saving
CO2 reduction
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Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
Original system Optimized scheme I Optimized scheme II Optimized scheme III Optimized scheme IV Optimized scheme V Optimized scheme VI Optimized scheme VII
(104 Yuan/y) 2.59 2.50 2.31 2.28 2.24 2.06 2.20 1.99
(kWh/y) 39801.60 38448.00 35568.00 35121.60 34488.00 31766.40 33868.80 30672.00
(104 Yuan/y) 0.09 0.28 0.30 0.35 0.52 0.39 0.59
(t/y) 35.46 34.25 31.68 31.29 30.72 28.30 30.17 27.32
(kWh/y) 1353.60 4233.60 4680.00 5313.60 8035.20 5932.80 9129.60
(t/y) 1.21 3.77 4.17 4.73 7.16 5.28 8.13
3. Evaluation methodology and model analysis 3.1. Analytic hierarchy process There are seven optimized schemes of air-condition system, which need to be evaluated comprehensively and objectively based on Analytic Hierarchy Process (AHP). AHP includes four steps. ķ Build the hierarchical model. Model the problem as a hierarchy containing the decision goal, the alternatives for reaching it, and the criteria for evaluating the alternatives. ĸ Build judgment matrix. Establish priorities among the elements of the hierarchy by making a series of judgments based on pairwise comparisons of the elements. Nine-digit percentage of the scale is set up when making comparison between two elements. Table 4 gives the value of scale for comparing two elements. Table 4. The value of scale for comparing two elements A over B
Extremely important
Very important
important
Somewhat important
Equivalent
minor slightly
minor
Very minor
Extremely minor
Value of A
9
7
5
3
1
1/3
1/5
1/7
1/9
Notes
8ǃ6ǃ4ǃ2ǃ1/2ǃ1/4ǃ1/6ǃ1/8 are the average values of A
Ĺ Check the consistency of the judgments. Consistency Index (C.I) of matrix is calculated by the following formula: OPD[ Q ˄1˅ & , Q Consistency Ratio (C.R) of the judgments is calculated by the following formula: & , ˄2˅ & 5 5 ,
Where, n is the matrix order; λmax is the maximum feature value of the matrix; R.I is the random consistency index, as shown in table 5. Table 5. Random consistency index (R.I) n
1
2
3
4
5
6
7
8
9
10
11
R.I
0
0
0.58
0.9
1.12
1.24
1.32
1.41
1.45
1.49
1.51
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Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
When C.R <0.10, it is considered that the consistency of judgment matrix is acceptable, otherwise some changes have to be adjusted for the judgments matrix. ĺ Come to a final decision based on the results of this process. Arrange the order of the elements according the factors weight. 3.2. Model analysis Figure 3 shows the evaluated model of central air-condition system using AHP. The top layer of model is to select an optimal central air-condition system; the middle layer of model is the guideline of the system, which includes economics, energy saving potential and CO2 emission; the bottom layer of model is the seven optimized schemes. Select an optimized scheme
Goal
Guideline
Energy saving
Economics
CO2 emission
Scheme I, scheme II, scheme III, scheme IV, scheme V, scheme VI and scheme VII
Schemes
Fig. 3. Evaluated model of optimal schemes
Construction matrix A is built of middle layer over to top layer; Construction matrix B 1(7), B2(7)and B3(7) are built of bottom layer over to middle layer according the results of table 3. The factor weight ω of seven optimal schemes is calculated by normalization process. ª º , « » » « « » ¬ ¼
$
B1
(7)
ª «1 « «3 « «7 « « «5 « «9 « « «6 « ¬9
1 3
1 7 1 5
1 5 1 2
5
1
1
2
1
1
3
3
4
1
3
2
3
7
5
5
1 9 1 3 1 3 1 4
1 6 1 3 1 2 1 3
1
3
1 3 3
1 3
1º 9» ˈ 1» » 7» 1» 5» (7) B2 1» » 5» 1» 3» 1» » 3» 1¼
ª «1 « «3 « «3 « « «4 « «7 « « «4 « ¬9
1 3
1 3
1 4 1 2 1 2
1
2
1 2
1
2
2
1
5
5
3
3
3
2
7
7
7
1 7 1 5 1 5 1 3
1 4 1 3 1 3 1 2
1
5
1 5 3
1 5
1º 9» , 1» » 7» 1» 7» (7) 1 » B3 » 7» 1» 3» 1» » 5» 1¼
ª «1 « «3 « «4 « « «4 « «7 « « «5 « ¬9
1 3
1 4 1 2
1 4 1 2
2
1
1
2
1
1
7
5
3
1
4
3
2
7
5
5
1 7 1 7 1 5 1 3
1 5 1 4 1 3 1 2
1
3
1 3 3
1 3
1º 9» 1» , » 7» 1» Z 5» 1» » 5» 1» 3» 1» » 3» 1¼
ªº « » « » « » « » « » «» « » «» « » ¬ ¼
The percentage of factor weight for seventh optimized scheme is of highest value 39.06%. The best scheme is to increase chilled, air supplied temperature difference and set up indoor temperature to 10ć, 9.8ć and 27ć by pump, compressor frequency conversion technologies and enhancing awareness of energy conservation. The factor weights of seven schemes from high to low are scheme VII, scheme V 23.25%, scheme VI 13.36%, scheme IV 8.99%, scheme III 7.89%, scheme II 5.09% and scheme I 2.36%.
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Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
4. Conclusions The energy consumption of air-condition system is affected by evaporation temperature, condenser temperature and pump head. The electricity consumption of refrigerator unit is of the largest percentage of 33% in the central air-condition system. The water transfer system, air supplied system and terminal unit equipment is of the percentage of 67%. Some conclusions are obtained based on numerical analysis. (1) Seven optimized schemes are designed for central air-condition system. The best scheme is to increase chilled, air supplied temperature difference and set up indoor temperature to 10ć, 9.8ć and 27ć by pump, compressor frequency conversion technologies and enhancing awareness of energy conservation, which will save power and CO2 emission 9200 kWh and 8.13 t per year. (2) It can be saved the energy consumption effectively to set up design operation parameters reasonably.it can save 4680 kWh of electricity consumption by increasing indoor temperature 1ć in the case of central air-condition system. (3) The factor weights of different optimized schemes are related to energy saving technologies. The maximum and minimum factor weights are 39.06% and 2.36% in the case of central air-condition system. 5. Copyright Authors keep full copyright over papers published in Energy Procedia Acknowledgements The paper is support by Guangdong province science and technology project (No. 2013B091500087). References [1] Li Zhaojian, Jiang Yi. Analysis on cooling energy consumption of residential buildings in China' s urban areas[J]. HV&AC. 2009, 39(5): 82-88. [2] Zhang Enxiang, Li Chunwang. Energy Consumption Evaluation and Energy -saving Potential Analysis of the HVAC System for an Office Building in China[J] . ENERGY CONSERVATION TECHNOLOGY,2008, 26˄150˅˖295-320 [3] Pu Qingping. Research on Prediction Model and Influencing Factors of Urban Residential Building Energy Consumption[D]. Doctor Dissertation of Chongqing university. 2012. [4] Ma Mingming. Research on Energy Efficiency Alteration and Potential of Air-Condition System of Public Building [D]. Master Dissertation of Chongqing University. 2007. [5] Zhu Weifeng, Jiang Yi. Analysis of common problems in refrigerating stations and air conditioning systems[J]. HV&AC. 2000, 30 (6):4-11. [6] Yang Changzhi, Wu Xiaoyan. Energy consumption status and energy saving potentials of air conditioning systems in public buildings of Changsha [J]. HV&AC. 2005, 35 (12):39-43.
Biography Luo Chao, assistant professor, mainly focus on building energy efficiency, geothermal power system and mid-low grade waste heat utilization.
ScienceDirect Energy Procedia 105 (2017) 2095 – 2100
The 8th International Conference on Applied Energy – ICAE2016
The Comprehensive Evaluation of Optimization AirCondition System Based on Analytic Hierarchy Methodology Luo Chaoa,b,c,d*, Lu Zhennenga,b,c, Gong Yuliea,b,c , Ma Zhitonga,b,c a
Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China b Key Laboratory of Renewable Energy, Chinese Academy of Science, Guangzhou 510640, China c Guangdong Key Laboratory of New and Renewable Energy Research and Development, Guangzhou 510640, China d Key Laboratory of Efficient Utilization of Low and Medium Grade Energy (Tianjin University), Ministry of Education, Tianjin 300072, China
Abstract The paper presents different kinds of optimization scheme of air-condition system based on equipment technologies and variable parameters in Guangzhou. Coefficients of performance (COP) and energy efficiency of rate (EER) are the main index of air-condition system. The results show that the percentage of optimized air-condition systems are of different weight ratio based on analytic hierarchy process method. Pump and compressor frequency conversion technologies and higher indoor temperature are the main energy efficiency measurements for air-condition system. The results provide a new methodology for evaluating the air conditioning system construction. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
© 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection peer-review of under responsibility of ICAE Peer-reviewand/or under responsibility the scientific committee of the 8th International Conference on Applied Energy. Keywords: air condition system; office building; Analytic Hierarchy Process (AHP); energy-saving potential; optimized design
1. Introduction Air-condition energy consumption accounts for 30% -60% of building energy consumption based on testing of hotel and supermarket in Beijing [1-2]. The building energy consumption includes the envelope heat losses; air-condition electricity consumption and lighting energy consumption. The energy saving potential of air-condition system is evaluated by testing and numerical calculation in China [3-4]. However, there are some problems of air-condition system, such as unreasonable design system, low efficiency of COP and irregular management [5-6].
* Corresponding author. Tel.:+086-020-87058428; fax: +086-020-87057791. E-mail address: [email protected].
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. doi:10.1016/j.egypro.2017.03.589
2096
Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
The paper presents seven optimized air-condition systems, and the economic and energy efficiency of the optimized systems are compared. The factors weights are calculated based on Analytic Hierarchy Process (AHP). 2. Optimized design and energy potential analysis of air-condition system The office building is built in the south of China. The width, length and height of the building are 10 meters, 30 meters and 9 meters. Figure 1 shows the physical model of the building. The first and second floor is supplied chilled air by unit-conditioner, and the third floor is supplied chilled air by central airconditioner. N
Fig. 1. Building physical model
The central air-condition system includes heat/cooled source, water and air transfer system and terminal equipment. In original central air-condition system, the indoor temperature is 26ć, supply air temperature difference between supply air and return air is 7 ć, cold water temperature difference between inlet and outlet is 5ć, cooling water temperature difference between inlet and outlet is 5ć. Table 1 shows the basic data of original central air-condition system. Table 1. Basic data of original central air-condition system Rated cooling capacity (Kw) 50
Parasitic work power (kW) 27.64
CO2 emission per kWh (kg/kWh) 0.8908
Electricity price per kWh (RMB/kWh) 0.65
Operation hours per year (h) 1440
Seven optimal central air-condition schemes are designed from the view of easing operability principles. The measurements include equipment technologies and parameters adjustment. The first optimized scheme is to increase chilled water temperature difference to 10 ć by pump frequency conversion technologies. The second optimized scheme is to increase supplied air temperature difference to 9.8ć by compressor frequency conversion technologies. The third optimized scheme is to set up indoor temperature to 27ć by enhancing the people awareness of energy conservation. The forth optimized scheme is combination of the first scheme and the second scheme. That is to increase chilled water and supplied air temperature difference to 10ć and 9.8ć by pump and compressor frequency conversion technologies. The fifth optimized scheme is combination of the second scheme and the third scheme. That is to increase supplied air temperature difference and set up indoor temperature to 9.8 ć and 27 ć by compressor frequency conversion technologies and enhancing awareness of energy conservation.
2097
Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
The sixth optimized scheme is combination of the first scheme and the second scheme. That is to increase chilled temperature difference and set up indoor temperature to 10 ć and 27ć by pump frequency conversion technologies and enhancing awareness of energy conservation. The seventh optimized scheme is combination of the first scheme, the second scheme and third scheme. That is to increase chilled, air supplied temperature difference and set up indoor temperature to 10ć, 9.8ć and 27ć by pump, compressor frequency conversion technologies and enhancing awareness of energy conservation. Figure 2 gives the topology diagram of seven optimized schemes. Energy saving technologies
Energy saving technologies of transfer system
Energy saving technologies of heat and chilled source
Optimized scheme II O
Optimized scheme I
Optimized scheme IV
Enhancing awareness of energy conservation
Optimized scheme III
Optimized scheme V
Optimized scheme I
Optimized scheme VI
Optimized scheme VII
Fig. 2. Topology diagram of seven optimized schemes
The performance indexes of central air-condition is calculated by Matlab software. Table 2 gives performance indexes of seven optimized schemes. The five performance indexes are coefficient of performance (COP), energy efficiency ratio (EER), water transfer factor of chilled water ( WTFchilled,water), water transfer factor of cooling water (WTFcooling,water) and indoor temperature. Table 2. Performance indexes of seven optimized schemes Optimized scheme Original system Optimized scheme I Optimized scheme II Optimized scheme III Optimized scheme IV Optimized scheme V Optimized scheme VI Optimized scheme VII
COP 4.105 4.114 3.448 4.382 3.455 3.667 4.392 3.676
EER 3.264 3.356 2.743 3.386 2.283 2.858 3.512 2.961
WTFchilled,water 30.4 43 26.46 29.16 37.42 25.5 41.25 36.06
WTFcooling,water 36.9 36.9 32.44 35.32 32.44 31.6 35.32 31.16
Indoor temperature (ć) 26 26 26 27 26 27 27 27
The energy saving potential comparisons between original and optimized systems is calculated. Table 3 shows the economics, electricity consumption and CO2 emission reduction of different systems. Scheme VII is the best optimized scheme, which can save electricity of 9200 kWh, operation cost of 5900 Yuan and CO2 emission 8.13 t per year. Table 3. Energy saving potential comparisons between original and optimized systems Operating costs
Electricity consumption
CO2 emission
Economics
Electricity saving
CO2 reduction
2098
Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
Original system Optimized scheme I Optimized scheme II Optimized scheme III Optimized scheme IV Optimized scheme V Optimized scheme VI Optimized scheme VII
(104 Yuan/y) 2.59 2.50 2.31 2.28 2.24 2.06 2.20 1.99
(kWh/y) 39801.60 38448.00 35568.00 35121.60 34488.00 31766.40 33868.80 30672.00
(104 Yuan/y) 0.09 0.28 0.30 0.35 0.52 0.39 0.59
(t/y) 35.46 34.25 31.68 31.29 30.72 28.30 30.17 27.32
(kWh/y) 1353.60 4233.60 4680.00 5313.60 8035.20 5932.80 9129.60
(t/y) 1.21 3.77 4.17 4.73 7.16 5.28 8.13
3. Evaluation methodology and model analysis 3.1. Analytic hierarchy process There are seven optimized schemes of air-condition system, which need to be evaluated comprehensively and objectively based on Analytic Hierarchy Process (AHP). AHP includes four steps. ķ Build the hierarchical model. Model the problem as a hierarchy containing the decision goal, the alternatives for reaching it, and the criteria for evaluating the alternatives. ĸ Build judgment matrix. Establish priorities among the elements of the hierarchy by making a series of judgments based on pairwise comparisons of the elements. Nine-digit percentage of the scale is set up when making comparison between two elements. Table 4 gives the value of scale for comparing two elements. Table 4. The value of scale for comparing two elements A over B
Extremely important
Very important
important
Somewhat important
Equivalent
minor slightly
minor
Very minor
Extremely minor
Value of A
9
7
5
3
1
1/3
1/5
1/7
1/9
Notes
8ǃ6ǃ4ǃ2ǃ1/2ǃ1/4ǃ1/6ǃ1/8 are the average values of A
Ĺ Check the consistency of the judgments. Consistency Index (C.I) of matrix is calculated by the following formula: OPD[ Q ˄1˅ & , Q Consistency Ratio (C.R) of the judgments is calculated by the following formula: & , ˄2˅ & 5 5 ,
Where, n is the matrix order; λmax is the maximum feature value of the matrix; R.I is the random consistency index, as shown in table 5. Table 5. Random consistency index (R.I) n
1
2
3
4
5
6
7
8
9
10
11
R.I
0
0
0.58
0.9
1.12
1.24
1.32
1.41
1.45
1.49
1.51
2099
Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
When C.R <0.10, it is considered that the consistency of judgment matrix is acceptable, otherwise some changes have to be adjusted for the judgments matrix. ĺ Come to a final decision based on the results of this process. Arrange the order of the elements according the factors weight. 3.2. Model analysis Figure 3 shows the evaluated model of central air-condition system using AHP. The top layer of model is to select an optimal central air-condition system; the middle layer of model is the guideline of the system, which includes economics, energy saving potential and CO2 emission; the bottom layer of model is the seven optimized schemes. Select an optimized scheme
Goal
Guideline
Energy saving
Economics
CO2 emission
Scheme I, scheme II, scheme III, scheme IV, scheme V, scheme VI and scheme VII
Schemes
Fig. 3. Evaluated model of optimal schemes
Construction matrix A is built of middle layer over to top layer; Construction matrix B 1(7), B2(7)and B3(7) are built of bottom layer over to middle layer according the results of table 3. The factor weight ω of seven optimal schemes is calculated by normalization process. ª º , « » » « « » ¬ ¼
$
B1
(7)
ª «1 « «3 « «7 « « «5 « «9 « « «6 « ¬9
1 3
1 7 1 5
1 5 1 2
5
1
1
2
1
1
3
3
4
1
3
2
3
7
5
5
1 9 1 3 1 3 1 4
1 6 1 3 1 2 1 3
1
3
1 3 3
1 3
1º 9» ˈ 1» » 7» 1» 5» (7) B2 1» » 5» 1» 3» 1» » 3» 1¼
ª «1 « «3 « «3 « « «4 « «7 « « «4 « ¬9
1 3
1 3
1 4 1 2 1 2
1
2
1 2
1
2
2
1
5
5
3
3
3
2
7
7
7
1 7 1 5 1 5 1 3
1 4 1 3 1 3 1 2
1
5
1 5 3
1 5
1º 9» , 1» » 7» 1» 7» (7) 1 » B3 » 7» 1» 3» 1» » 5» 1¼
ª «1 « «3 « «4 « « «4 « «7 « « «5 « ¬9
1 3
1 4 1 2
1 4 1 2
2
1
1
2
1
1
7
5
3
1
4
3
2
7
5
5
1 7 1 7 1 5 1 3
1 5 1 4 1 3 1 2
1
3
1 3 3
1 3
1º 9» 1» , » 7» 1» Z 5» 1» » 5» 1» 3» 1» » 3» 1¼
ªº « » « » « » « » « » «» « » «» « » ¬ ¼
The percentage of factor weight for seventh optimized scheme is of highest value 39.06%. The best scheme is to increase chilled, air supplied temperature difference and set up indoor temperature to 10ć, 9.8ć and 27ć by pump, compressor frequency conversion technologies and enhancing awareness of energy conservation. The factor weights of seven schemes from high to low are scheme VII, scheme V 23.25%, scheme VI 13.36%, scheme IV 8.99%, scheme III 7.89%, scheme II 5.09% and scheme I 2.36%.
2100
Luo Chao et al. / Energy Procedia 105 (2017) 2095 – 2100
4. Conclusions The energy consumption of air-condition system is affected by evaporation temperature, condenser temperature and pump head. The electricity consumption of refrigerator unit is of the largest percentage of 33% in the central air-condition system. The water transfer system, air supplied system and terminal unit equipment is of the percentage of 67%. Some conclusions are obtained based on numerical analysis. (1) Seven optimized schemes are designed for central air-condition system. The best scheme is to increase chilled, air supplied temperature difference and set up indoor temperature to 10ć, 9.8ć and 27ć by pump, compressor frequency conversion technologies and enhancing awareness of energy conservation, which will save power and CO2 emission 9200 kWh and 8.13 t per year. (2) It can be saved the energy consumption effectively to set up design operation parameters reasonably.it can save 4680 kWh of electricity consumption by increasing indoor temperature 1ć in the case of central air-condition system. (3) The factor weights of different optimized schemes are related to energy saving technologies. The maximum and minimum factor weights are 39.06% and 2.36% in the case of central air-condition system. 5. Copyright Authors keep full copyright over papers published in Energy Procedia Acknowledgements The paper is support by Guangdong province science and technology project (No. 2013B091500087). References [1] Li Zhaojian, Jiang Yi. Analysis on cooling energy consumption of residential buildings in China' s urban areas[J]. HV&AC. 2009, 39(5): 82-88. [2] Zhang Enxiang, Li Chunwang. Energy Consumption Evaluation and Energy -saving Potential Analysis of the HVAC System for an Office Building in China[J] . ENERGY CONSERVATION TECHNOLOGY,2008, 26˄150˅˖295-320 [3] Pu Qingping. Research on Prediction Model and Influencing Factors of Urban Residential Building Energy Consumption[D]. Doctor Dissertation of Chongqing university. 2012. [4] Ma Mingming. Research on Energy Efficiency Alteration and Potential of Air-Condition System of Public Building [D]. Master Dissertation of Chongqing University. 2007. [5] Zhu Weifeng, Jiang Yi. Analysis of common problems in refrigerating stations and air conditioning systems[J]. HV&AC. 2000, 30 (6):4-11. [6] Yang Changzhi, Wu Xiaoyan. Energy consumption status and energy saving potentials of air conditioning systems in public buildings of Changsha [J]. HV&AC. 2005, 35 (12):39-43.
Biography Luo Chao, assistant professor, mainly focus on building energy efficiency, geothermal power system and mid-low grade waste heat utilization.