Projection of future transport energy demand of Thailand
AbstractThe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Energy Policy.
Volume (Year): 39 (2011)
Issue (Month): 5 (May)
Contact details of provider:
Web page: http://www.elsevier.com/locate/enpol
Transportation energy consumption Neural network Log-linear model;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Zachariadis, Theodoros & Kouvaritakis, Nikos, 2003. "Long-term outlook of energy use and CO2 emissions from transport in Central and Eastern Europe," Energy Policy, Elsevier, vol. 31(8), pages 759-773, June.
- Wohlgemuth, Norbert, 1997. "World transport energy demand modelling : Methodology and elasticities," Energy Policy, Elsevier, vol. 25(14-15), pages 1109-1119, December.
- Yan, Xiaoyu & Crookes, Roy J., 2009. "Reduction potentials of energy demand and GHG emissions in China's road transport sector," Energy Policy, Elsevier, vol. 37(2), pages 658-668, February.
- Haldenbilen, Soner, 2006. "Fuel price determination in transportation sector using predicted energy and transport demand," Energy Policy, Elsevier, vol. 34(17), pages 3078-3086, November.
- , 2008. "Modelling aviation fuel demand: the case of the United States and China," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 32(4), pages 323-342, December.
- Schafer, Andreas, 1998. "The global demand for motorized mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(6), pages 455-477, August.
- Polemis, Michael L., 2006. "Empirical assessment of the determinants of road energy demand in Greece," Energy Economics, Elsevier, vol. 28(3), pages 385-403, May.
- Mohammad Mazraati & Osama M. Alyousif, 2009. "Aviation fuel demand modelling in OECD and developing countries: impacts of fuel efficiency," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 33(1), pages 23-46, 03.
- Dhakal, Shobhakar, 2003. "Implications of transportation policies on energy and environment in Kathmandu Valley, Nepal," Energy Policy, Elsevier, vol. 31(14), pages 1493-1507, November.
- Murat, Yetis Sazi & Ceylan, Halim, 2006. "Use of artificial neural networks for transport energy demand modeling," Energy Policy, Elsevier, vol. 34(17), pages 3165-3172, November.
- Pongthanaisawan, Jakapong & Sorapipatana, Chumnong, 2010. "Relationship between level of economic development and motorcycle and car ownerships and their impacts on fuel consumption and greenhouse gas emission in Thailand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 2966-2975, December.
- Ceylan, Huseyin & Ceylan, Halim & Haldenbilen, Soner & Baskan, Ozgur, 2008. "Transport energy modeling with meta-heuristic harmony search algorithm, an application to Turkey," Energy Policy, Elsevier, vol. 36(7), pages 2527-2535, July.
- Haldenbilen, Soner & Ceylan, Halim, 2005. "Genetic algorithm approach to estimate transport energy demand in Turkey," Energy Policy, Elsevier, vol. 33(1), pages 89-98, January.
- Bose, Ranjan Kumar & Srinivasachary, V, 1997. "Policies to reduce energy use and environmental emissions in the transport sector : A case of Delhi city," Energy Policy, Elsevier, vol. 25(14-15), pages 1137-1150, December.
- Lu, I.J. & Lewis, Charles & Lin, Sue J., 2009. "The forecast of motor vehicle, energy demand and CO2 emission from Taiwan's road transportation sector," Energy Policy, Elsevier, vol. 37(8), pages 2952-2961, August.
- 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.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.