Commenced in January 2007
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Edition: International
Paper Count: 30004
Decomposing the Impact Factors of Energy Consumption of Hotel through LMDI

Authors: Zongjie Du, Shulin Sui, Panpan Xu

Abstract:

Energy consumption of a hotel can be a hot topic in smart city; it is difficult to evaluate the contribution of impact factors to energy consumption of a hotel. Therefore, grasping the key impact factors has great effect on the energy saving management of a hotel. Based on the SPIRTPAT model, we establish the identity with the impact factors of occupancy rate, unit area of revenue, temperature factor, unit revenue of energy consumption. In this paper, we use the LMDI (Logarithmic Mean Divisia Index) to decompose the impact factors of energy consumption of hotel from Jan. to Dec. in 2001. The results indicate that the occupancy rate and unit area of revenue are the main factors that can increase unit area of energy consumption, and the unit revenue of energy consumption is the main factor to restrain the growth of unit area of energy consumption. When the energy consumption of hotel can appear abnormal, the hotel manager can carry out energy saving management and control according to the contribution value of impact factors.

Keywords: Smart city, SPIRTPAT model, LMDI, saving management and control.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1110822

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References:


[1] World Bank. Growth and CO2 Emissions: How Does India Compare to Other Countries? (R). India: Relationship between Growth and CO2 Emissions, 2007.
[2] Yuhui Ou, Yifang Liu, Jiangyi Man, The decomposition of energy consumption in our country based on LMDI method (J). Economic management, 2007, 29(7): 91-95.
[3] Fumin Liao, Research on industrial energy consumption decomposition based on LMDI method (J). Search, 2008, (8): 23-25.
[4] Liaoqing Wei, Dequn Zhou. Empirical analysis of the influence factors of energy consumption in Jiangsu Province based on LMDI method (J). Price monthly, 2009, (2): 51-54.
[5] Junsong Tu, Canchi He. Energy consumption, economic growth and the change of CO2 emissions in China-Analysis Based on LMDI method (J). Resources and environment in the Yangtze River Basin, 2010, 19(1): 18-23.
[6] Yuan Tu, Benyong Wei, Xiuqi Fang etc. Implicit carbon decomposition of China's international trade based on LMDI method (J). Population, resources and environment in China, 2011, 21(2): 141-146.
[7] Lu Jiang, Research on virtual water trade of China based on input output analysis (D). South China University of Technology, 2012.
[8] Ying Han, Ping Ma, Lu Liu. A new method of impact factors of energy consumption intensity (J). Quantitative economic technology and economic research, 2010(4): 137-147.
[9] F. Q. Zhang, B. W. Ang, Methodological issues in cross-country/ region decomposition of energy and environment indicators. Energy Economics 2001, 23(2), 179-190.
[10] B. W. Ang, Decomposition analysis for policymaking in energy: which is the preferred method? Energy Policy 2004, 32(9), 1131-1139.
[11] B. W. Ang, Na Liu, Handling zero values in the logarithmic mean Divisia index decomposition approach (J). Energy Policy, 2007, 35(1), 238-246.
[12] T. Dietz, E. A. Rosa, Rethinking the environmental impacts of population, affluence and technology (J). Human Ecology Review, 1994(1), 277-300.