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Future LNG competition and trade using an agent-based predictive model

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submitted on 2023-10-18, 10:46 and posted on 2023-10-18, 12:31 authored by Abel Meza, Ibrahim Ari, Mohammed Saleh Al-Sada, Muammer Koç

Liquified Natural Gas (LNG) is an alternative method to transport natural gas (NG), more versatile than pipeline gas, and helps increasing the availability, affordability and use of NG compared to carbon-intensive coal and oil. In the LNG market, various expansions projects have been planned and underway for the 2020s. Although some projects were put hold or delayed due to the demand shocks from the COVID-19 pandemic, the LNG market demonstrates the potential to expand further in the future. This study employs an Agent-Based Model (ABM) to evaluate these prospects of expansion in demand and supply, competition among various suppliers, and potential trade challenges in the coming decades. This model combines the usual contractual engagements of the LNG market and a representation of the spot market to simulate the possible traded quantities. The model is validated by comparing simulations with the historical record of the LNG trade in 2016 and 2018, reflecting its accuracy in replicating such real data. Proceeding with the results for the time horizon until 2030, the model represents the preponderance of Qatar as the most competitive LNG supplier, even when new LNG infrastructure comes online everywhere. The US is an emergent competitor with multiple projects finding demand in all the LNG regions, while Australia would still highly depend on the Asian Pacific basin. Other smaller exporters would struggle to find importing markets but collectively would open new regional markets. The model projects around 510+ MTPA of LNG trade by 2030, fairly similar to other projections.

Other Information

Published in: Energy Strategy Reviews
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.esr.2021.100734

Funding

Open Access funding provided by the Qatar National Library

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2021

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU

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