Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. KMITL
  3. Publication
  4. Energy Demand Modeling for the Eastern Economic Corridor of Thailand: A Case Study of Rayong Province
Loading...
Thumbnail Image

Energy Demand Modeling for the Eastern Economic Corridor of Thailand: A Case Study of Rayong Province

Author(s)
Lunsamrong, Chanidaporn
Tippichai, Atit
Date Issued
March 20, 2022
Type
Article
DOI
10.32479/ijeep.12884
Abstract
This paper assesses long-term energy consumption and greenhouse gas (GHG) emissions in Rayong Province which is one of the three provinces in the Eastern Economic Corridor (EEC) of Thailand. LEAP (the low emissions analysis platform) is used to project final energy demand for each economic sector by using the 2019 data as a base year. In the model, we defined the energy consumption into two scenarios; a business-as-usual (BAU) scenario and a low carbon scenario (LCS), to see different energy demand and CO2 emissions up to the year 2050. There are different assumptions between BAU and LCS in each sector such as energy efficiency improvement, shift to modern energy, the share of high energy-efficient vehicles, etc. In the BAU scenario, the final energy consumption needed by Rayong Province will increase with an average annual growth rate (AAGR) of 3.49%, while only 1.52% for the LCS. CO2 emissions in the LCS will be reduced by 41.7% by 2050 when compared with the BAU scenario. Most interestingly, even though energy demand in Rayong Province will be increasing up to 2050, CO2 emissions will peak about 2035 and then reduce. The industry and transport sectors are the most final energy consumption and the highest CO2 emissions. This is because EEC is driven by a production-based economy. The solution for this is to transform to alternative energies sourcing, shift all productions to sustainable ones, restructure the industrial estate to become the eco-industrial and GHG emissions management, which will also result in obvious carbon reduction. This kind of information will be beneficial to energy demand conservation and GHG emission mitigation at the provincial level which will depend on the energy policies initiated and implemented in the future.
Citation
International Journal of Energy Economics and Policy, 12(2), 497-501, 2022
Subjects

CO2 Emissions

Energy Demand Modelin...

Greenhouse Gas

Low Carbon City

Scenario Analysis

Thailand

Metrics
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your Institution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback