دورية أكاديمية

Malaysia energy outlook from 1990 to 2050 for sustainability: Business-as-usual and Alternative-policy Scenarios based economic projections with AI based experiments

التفاصيل البيبلوغرافية
العنوان: Malaysia energy outlook from 1990 to 2050 for sustainability: Business-as-usual and Alternative-policy Scenarios based economic projections with AI based experiments
المؤلفون: Mohammad Kamrul Hasan, Musse Mohamud Ahmed, Shayla Islam, S. Rayhan Kabir, Mousa'b Shtayat, Fatima Rayan Awad Ahmed, Mufti Mahmud, Mohd Zakree Ahmad Nazri, Nissrein Babiker Mohammed Babiker
المصدر: Energy Strategy Reviews, Vol 53, Iss , Pp 101360- (2024)
بيانات النشر: Elsevier, 2024.
سنة النشر: 2024
مصطلحات موضوعية: Energy demand, Sustainable energy, Energy economics, LSTM, Renewable energy, Smart energy, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
الوصف: Energy-outlook from past to future specific years has become essential in energy-economy. Malaysia is a member of ASEAN (Association of South-east Asian Nations), and ASEAN is increasing the use of renewable energy by 2050 to reduce carbon dioxide (CO2) emissions. Coal is Malaysia's primary fossil fuel for energy generation, producing large amounts of CO2 and exacerbating greenhouse problems, including air pollution. Moreover, renewable energy capacity has increased significantly worldwide since 2020 during the COVID-19 pandemic. Therefore, this study provides an energy-outlook study from 1990 to 2050 as a rationale for Malaysia's emphasis on sustainable energy in the post-COVID-19 years, which has been felt to be absent in previous studies. Here, past data as well as projections of future coal trade, hydropower growth, electricity consumption, renewable energy consumption, and CO2 emissions are shown. An energy-outlook procedure is explored by reviewing the literature to derive data visualizations and projections. Business-as-usual (BAU) and Alternative-policy Scenarios (APS) methods have been used for projections. The article prioritizes coal since coal is the main fossil fuel for electricity generation in Malaysia. The study observed a significant increase in CO2 emissions with increasing energy demand in Malaysia, which is a concern, and the article emphasized the importance of renewable energy in mitigating CO2 emissions. Finally, Long-short-term memory (LSTM) has been used as an initial experiment on how Artificial Intelligence (AI) can be used in the energy outlook study, which indicates the research scope of AI.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2211-467X
Relation: http://www.sciencedirect.com/science/article/pii/S2211467X24000671; https://doaj.org/toc/2211-467X
DOI: 10.1016/j.esr.2024.101360
URL الوصول: https://doaj.org/article/a7ffa13cbdaf4fca99b8577f5628dd02
رقم الأكسشن: edsdoj.7ffa13cbdaf4fca99b8577f5628dd02
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2211467X
DOI:10.1016/j.esr.2024.101360