LAPSE:2023.20412
Published Article
LAPSE:2023.20412
Conventional Natural Gas Project Investment and Decision Making under Multiple Uncertainties
Chi Yong, Mu Tong, Zhongyi Yang, Jixian Zhou
March 17, 2023
Abstract
Similar to many energy projects, the evaluation of investments in natural gas projects is influenced by technical and economic uncertainties. These uncertainties include natural resource characteristics, production, decline laws, prices, taxes, benchmark yield, and so on. In China, conventional natural gas is still the dominant energy source. The investors are mainly large state-owned energy companies. Therefore, it is necessary to include the technical and economic uncertainties, as well as the investment decision and optimization problems of the enterprises in a unified analytical framework. To this end, this paper innovatively constructs such a framework. Using numerical simulations of approaches, the process of investment decision optimization by companies based on technology assessment and price forecasting is visualized in detail. The results suggest that the investment decision of the enterprise needs to consider technical and economic uncertainties in an integrated manner. It also needs to combine the business strategy and social responsibility of the enterprise in order to construct the objective function. With the availability of data, the framework and its algorithms can be used for practical evaluation of investment plans and decision supports for conventional natural gas projects. The framework can also integrate the analytical perspective of the macroeconomic and political environment to bring in a more comprehensive range of uncertainties.
Keywords
economic evaluation, natural gas project, numerical simulation, technology and economy, uncertainties
Suggested Citation
Yong C, Tong M, Yang Z, Zhou J. Conventional Natural Gas Project Investment and Decision Making under Multiple Uncertainties. (2023). LAPSE:2023.20412
Author Affiliations
Yong C: College of Logistics, Chengdu University of Information Technology, Chengdu 610225, China [ORCID]
Tong M: School of Finance, Southwest University of Finance and Economics, Chengdu 611130, China
Yang Z: School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China
Zhou J: School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China
Journal Name
Energies
Volume
16
Issue
5
First Page
2342
Year
2023
Publication Date
2023-02-28
ISSN
1996-1073
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Original Submission
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PII: en16052342, Publication Type: Journal Article
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LAPSE:2023.20412
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https://doi.org/10.3390/en16052342
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