DocumentCode :
507297
Title :
Regional Energy Demand Modeling and Forecasting
Author :
Hang, Yu ; Deyun, Xiao ; Zhentao, Liu
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume :
5
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
599
Lastpage :
603
Abstract :
Because of the essential role played by energy in economic development, particularly in view of the two major global energy crises and recent high oil prices, whether or not a region or the whole world can successfully satisfy its energy demand has been an issue of great importance. This study uses stochastic models to forecast regional energy demand in the situation of insufficient statistical data. Autoregressive integrated moving average (ARIMA) model needs less data than other models and can represent economic time series well. So we use it in this study and apply it to the case of Taiwan. The study concludes that there will be an average annual growth of 3.1% for Taiwan´s total energy demand during 2008-2012, and we suggests more cross-strait energy cooperation.
Keywords :
autoregressive moving average processes; load forecasting; stochastic processes; time series; autoregressive integrated moving average model; cross-strait energy cooperation; economic development; energy demand; regional energy demand modeling; statistical data; stochastic models; Demand forecasting; Economic forecasting; Economic indicators; Fuel economy; Load forecasting; Petroleum; Power generation economics; Predictive models; Stochastic processes; Time series analysis; ARIMA; energy demand; forecast; stochastic models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
Type :
conf
DOI :
10.1109/FSKD.2009.177
Filename :
5360553
Link To Document :
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