RESEARCH ARTICLE

Multiple regression models for energy consumption of office buildings in different climates in China

  • Siyu ZHOU ,
  • Neng ZHU
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  • School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China

Received date: 12 Sep 2012

Accepted date: 01 Nov 2012

Published date: 05 Mar 2013

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg

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.

Cite this article

Siyu ZHOU , Neng ZHU . Multiple regression models for energy consumption of office buildings in different climates in China[J]. Frontiers in Energy, 2013 , 7(1) : 103 -110 . DOI: 10.1007/s11708-012-0220-z

1
Cai W G, Wu Y, Zhong Y, Ren H. China building energy consumption: Situation, challenges and corresponding measures. Energy Policy, 2009, 37(6): 2054-2059

DOI

2
Jiang Y, Wu X. 2010 Annual Report on China Building Energy Efficiency. Beijing: China Architecture & Building Press, 2010

3
Kong X F, Lu S L, Wu Y. A review of building energy efficiency in China during “Eleventh Five-year Plan” period. Energy Policy, 2012, 41: 624-635

DOI

4
Jie P F, Tian Z, Yuan S S.Modeling the dynamic characteristics of a district heating network. Energy, 2012, 39: 126-134

5
Chang C C, Zhao J, Zhu N. Energy saving effect prediction and post evaluation of air-conditioning system in public buildings. Energy and Building, 2011, 43(11): 3243-3249

DOI

6
Zhao J, Xin Y J, Tong D D. Energy consumption quota of public buildings based on statistical analysis. Energy Policy, 2012, 43: 362-370

DOI

7
Jie P F, Li D Y, Zhu N.Optimization of regulation methods in district heating systems. Advanced Materials Research, 2012, 490: 1475-1480

8
Xie Z G, Hong H B, Li S Y. Interference effects of high-rise buildings: Effects of building shapes and correlations of envelope interference factors. Journal of Building Structures, 2008, 29(1): 13-18

9
Carlo J, Lamberts R. Development of envelope efficiency labels for commercial buildings: Effect of different variables on electricity consumption. Energy and Building, 2008, 40(11): 2002-2008

DOI

10
Lam J C, Wan K K W, Liu D L, Tsang C L. Multiple regression models for energy use in air-conditioned office buildings in different climates. Energy Conversion and Management, 2010, 51(12): 2692-2697

DOI

11
Catalina T, Virgone J, Blanco E. Development and validation of regression models to predict monthly heating demand for residential buildings. Energy and Building, 2008, 40(10): 1825-1832

DOI

12
Li D H W, Wong S L, Cheung K L. Energy performance regression models for office buildings with daylighting controls. Journal of Power and Energy, 2008, 222(6): 557-568

DOI

13
Lam J C, Tsang C L, Li D H W, Cheung S O. Residential building envelope heat gain and cooling energy requirements. Energy, 2005, 30(7): 933-951

DOI

14
Xu X H, Wang S W. Optimal simplified thermal models building envelope based on frequency domain regression using genetic algorithm. Energy and Building, 2007, 39(5): 525-536

DOI

15
Jaffal L, Inard C, Ghiaus C. Fast method to predict building heating demand based on the design of experiments. Energy and Building, 2009, 41(6): 669-677

DOI

16
Kim Y M, Lee J H, Kim S M, Kim S. Effects of double skin envelopes on natural ventilation and heating loads in office buildings. Energy and Building, 2011, 43(9): 2118-2126

DOI

17
Ministry of Housing and Urban-Rural Deveiopment of the People’s Republic of China, General Administration of Quality Supervision, Inspection and Quarantine. GB50176-93 Thermal Design Code for Civil Buildings. Beijing: China Architecture & Building Press, 1993

18
Ministry of Housing and Urban-Rural Deveiopment of the People’s Republic of China, General Administration of Quality Supervision, Inspection and Quarantine. GB50365-2005 Design Standard for Energy Efficiency of Public Buildings. Beijing: China Architecture & Building Press, 2005

19
Cheung C K, Fuller R J, Luther M B. Energy-efficient envelope design for high-rise apartments. Energy and Building, 2005, 37(1): 37-48

DOI

20
Tzempelikos A, Athienitis A K, Karava P. Simulation of façade and envelope design options for a new institutional building. Solar Energy, 2007, 81(9): 1088-1103

DOI

21
Farhanieh B, Sattari S. Simulation of energy saving in Iranian buildings using integrative modelling for insulation. Renewable Energy, 2006, 31(4): 417-425

DOI

22
Lee W S. Benchmarking the energy efficiency of government buildings with data envelopment analysis. Energy and Building, 2008, 40(5): 891-895

DOI

23
Karaguzel O T, Lam K P. Development of whole-building energy performance models as benchmarks for retrofit projects. In: Proceedings of the 2011 Winter Simulation Conference. Phoenix: IEEE, 2011, 838-849

24
Xiong A Y, Wang B M. Meteorological Data Sets on Building Thermal Environment Analysis. Beijing: China Architecture & Building Press, 2005

25
General Administration of Quality Supervision, Inspection and Quarantine, Standardization Administration of the People’s Republic of China. GB/T2589-2008 Calculation Principle of Comprehensive Energy Consumption. Beijing: China Standard Press, 2008

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