Modeling of electricity consumption in the Asian gaming and tourism center - Macao SAR, people's republic of China

被引:37
作者
Lai, T. M. [1 ]
To, W. M. [1 ]
Lo, W. C. [2 ]
Choy, Y. S. [3 ]
机构
[1] Macao Polytech Inst, Sch Business, Macau, Peoples R China
[2] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
[3] Hong Kong Polytech Univ, Dept Mech Engn, Hong Kong, Hong Kong, Peoples R China
关键词
electricity consumption; multiple regression; artificial neural network; wavelet ANN;
D O I
10.1016/j.energy.2007.12.007
中图分类号
O414.1 [热力学];
学科分类号
摘要
The rise of electricity is indispensable to modern life. As Macao Special Administrative Region becomes a gaining and tourism center in Asia, modeling the consumption of electricity is critical to Macao's economic development. The purposes of this paper are to conduct an extensive literature review on modeling of electricity consumption, and to identify key climatic, demographic, economic and/or industrial factors that may affect the electricity consumption of a country/city. It was identified that the five factors, namely temperature, population, the number of tourists, hotel room occupancy and days per month, could be used to characterize Macao's monthly electricity consumption. Three selected approaches including multiple regression, artificial neural network (ANN) and wavelet ANN were used to derive mathematical models of the electricity consumption. The accuracy of these models was assessed by using the mean squared error (MSE), the mean squared percentage error (MSPE) and the mean absolute percentage error (MAPE). The error analysis shows that wavelet ANN has a very promising forecasting capability and can reveal the periodicity of electricity consumption. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:679 / 688
页数:10
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