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Projection of future transport energy demand of Thailand

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  • Limanond, Thirayoot
  • Jomnonkwao, Sajjakaj
  • Srikaew, Artit
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    Abstract

    The objective of this study is to project transport energy consumption in Thailand for the next 20 years. The study develops log-linear regression models and feed-forward neural network models, using the as independent variables national gross domestic product, population and the numbers of registered vehicles. The models are based on 20-year historical data between years 1989 and 2008, and are used to project the trends in future transport energy consumption for years 2010-2030. The final log-linear models include only gross domestic product, since all independent variables are highly correlated. It was found that the projection results of this study were in the range of 54.84-59.05 million tonnes of oil equivalent, 2.5 times the 2008 consumption. The projected demand is only 61-65% of that predicted in a previous study, which used the LEAP model. This major discrepancy in transport energy demand projections suggests that projects related to this key indicator should take into account alternative projections, because these numbers greatly affect plans, policies and budget allocation for national energy management.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 39 (2011)
    Issue (Month): 5 (May)
    Pages: 2754-2763

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    Handle: RePEc:eee:enepol:v:39:y:2011:i:5:p:2754-2763

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    Web page: http://www.elsevier.com/locate/enpol

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    Keywords: Transportation energy consumption Neural network Log-linear model;

    References

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    Cited by:
    1. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    2. Geem, Zong Woo, 2011. "Transport energy demand modeling of South Korea using artificial neural network," Energy Policy, Elsevier, vol. 39(8), pages 4644-4650, August.
    3. Al-Ghandoor, Ahmed & Jaber, Jamal & Al-Hinti, Ismael & Abdallat, Yousef, 2013. "Statistical assessment and analyses of the determinants of transportation sector gasoline demand in Jordan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 129-138.

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