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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

Postal Subscription Code 80-972

2018 Impact Factor: 1.701

Front Energ    2013, Vol. 7 Issue (1) : 103-110    https://doi.org/10.1007/s11708-012-0220-z
RESEARCH ARTICLE
Multiple regression models for energy consumption of office buildings in different climates in China
Siyu ZHOU(), Neng ZHU
School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
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Abstract

The energy consumption of office buildings in China has been growing significantly in recent years. Obviously, there are significant relationships between building envelope and the energy consumption of office buildings. The 8 key building envelope influencing factors were found in this paper to evaluate their effects on the energy consumption of the air-conditioning system. The typical combinations of the key influencing factors were performed in Trnsy simulation. Then on the basis of the simulated results, the multiple regression models were developed respectively for the four climates of China—hot summer and warm winter, hot summer and cold winter, cold, and severely cold. According to the analysis of regression coefficients, the appropriate building envelope design schemes were discussed in different climates. At last, the regression model evaluations consisting of the simulation evaluations and the actual case evaluations were performed to verify the feasibility and accuracy of the regression models. The error rates are within±5% in the simulation evaluations and within±15% in the actual case evaluations. It is believed that the regression models developed in this paper can be used to estimate the energy consumption of office buildings in different climates when various building envelope designs are considered.

Keywords regression model      energy consumption      building envelope      office building      different climates     
Corresponding Author(s): ZHOU Siyu,Email:zsyhm1015@sina.com   
Issue Date: 05 March 2013
 Cite this article:   
Siyu ZHOU,Neng ZHU. Multiple regression models for energy consumption of office buildings in different climates in China[J]. Front Energ, 2013, 7(1): 103-110.
 URL:  
https://academic.hep.com.cn/fie/EN/10.1007/s11708-012-0220-z
https://academic.hep.com.cn/fie/EN/Y2013/V7/I1/103
ClimateRepresentative cityHDD18CDD26Solar radiation/(MJ· m-2·a-1)
Hot summer and warm winterShenzhen3942834087
Hot summer and cold winterShanghai15861364579
Cold regionBeijing2795715042
Severe cold region Shenyang4007154739
Tab.1  Representative cities of the four climates
ComponentsConfigurationU-value/(W·m-2·K-1)
Exterior walls200 mm reinforced concrete3.06
Roof100 mm reinforced concrete3.72
Ground300 m compacted clay1.64
200 mm gravel concrete
Window framesAluminum alloy frame6.21
Window glazing4 mm single clear glazing5.68
Tab.2  Configurations and U-values of building envelopes
ParametersValues
Air-conditioning design temperature/·C26
Air-conditioning design moisture/%60
Heating design temperature/ ·C20
Infiltration/(AC·h-1)0.2
Lighting load/(W·m-2)13
Equipment load/(W·m-2)20
Person load (light work)/person480
Tab.3  Parameters of office building model
Building envelope influence factorsBase caseLevel 1Level 2Level 3
Uwall/(W?m-2 ? K-1)3.060.5320.4470.369
Uroof/(W?m-2 ? K-1)3.720.6280.4840.375
Uglazing/(W?m-2 ? K-1)5.682.832.762.57
Uframe/(W?m-2 ? K-1)6.213.1--
SHGC0.8550.7550.4050.599
SRR0.0750.1260.1110.221
ISC00.20.50.7
ESC00.30.71
Tab.4  Different levels of building envelope influence factors
Regression coefficientCity
ShenzhenShanghaiBeijingShenyang
k1-0.3431.9083.0684.250
K2-0.5190.7601.024
K3-0.5371.5022.4843.499
K4---0.82
K54.4960.294-0.603-1.630
K6-8.4030.8031.8092.374
K7-0.794-0.423-0.363-
K8-0.271-0.152-0.137-
C33.41719.06121.93526.847
R20.8850.9570.9610.962
Standard error/(kW·h·m-2)0.3150.6721.0341.417
Tab.5  Regression coefficients of 8 key building envelope influence factors
Fig.1  Comparisons between regression-predicted and Trnsys-simulated energy consumption indexes
(a) Shenzhen; (b) Shanghai; (c) Beijing; (d) Shenyang
Influence factorsCity
ShenzhenShanghaiBeijingShenyang
Uwall/(W·m-2 ·K-1)1.121.020.60.51
Uroof /(W·m-2 ·K-1)0.6270.540.450.25
Uglazing/(W·m-2 ·K-1)2.572.572.502.20
Uframe/(W·m-2 ·K-1)3.12.82.72.6
SHGC0.5630.5820.6100.567
SRR0.2470.2400.2640.223
ISC0.5000.3
ESC0.70.70.50.5
Tab.6  Values of 8 key building envelope influence factors in research cases
Energy consumption indexCity
ShenzhenShanghaiBeijingShenyang
Actual energy consumption/(kW·h·m-2)30.729.232.841.9
Regression results/(kW·h·m-2)31.525.430.438.7
Error rate/%2.6-13.0-7.3-7.6
Tab.7  Comparisons of actual energy consumption indexes and regression results
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