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International Journal of Energy Economics and Policy
Article . 2022 . Peer-reviewed
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https://dx.doi.org/10.60692/ms...
Other literature type . 2022
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https://dx.doi.org/10.60692/09...
Other literature type . 2022
Data sources: Datacite
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Energy Demand Modeling for the Eastern Economic Corridor of Thailand: A Case Study of Rayong Province

نمذجة الطلب على الطاقة للممر الاقتصادي الشرقي لتايلاند: دراسة حالة لمقاطعة رايونغ
Authors: Atit Tippichai; Chanidaporn Lunsamrong;

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

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.

Keywords

LEAP, Economics, CO2 emissions, Energy industries. Energy policy. Fuel trade, Greenhouse gas, Scenario analysis, Environmental science, energy demand modeling, Engineering, Natural resource economics, Sociology, GE1-350, Efficient energy use, Business, Global Energy Demand, Rebound Effect on Energy Efficiency and Consumption, Biology, Agricultural economics, Energy, Ecology, Renewable Energy, Sustainability and the Environment, scenario analysis, Social science, FOS: Sociology, Environmental sciences, Energy consumption, Consumption (sociology), greenhouse gas, FOS: Biological sciences, Electrical engineering, Physical Sciences, HD9502-9502.5, low carbon city, Finance

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