Reliability allocation method for natural gas pipelines considering hydrothermal processes for pipeline natural gas transmission

Shiliang Peng; Huai Su; Xiao Wang

doi:10.1117/12.3000040

23 August 2023 Reliability allocation method for natural gas pipelines considering hydrothermal processes for pipeline natural gas transmission

Shiliang Peng, Huai Su, Xiao Wang

Author Affiliations +

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127842D (2023) https://doi.org/10.1117/12.3000040
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

Reliability allocation is a direct means to improve the reliability of natural gas pipeline gas supply, but the current natural gas pipeline reliability allocation method does not consider the hydrothermal process of pipeline natural gas transmission. Therefore, a natural gas pipeline reliability allocation method is proposed in this paper. First, based on the physical model of the pipeline system, a mapping model between the state of the compressor station and the reliability of the system gas supply is established with the help of Monte Carlo simulation; the reliability of the compressor station is optimally allocated with the objective of minimizing the system operation cost, and solved by using GA(Genetic Algorithm). Finally, the proposed model is applied to a real-world data from a pipeline system in China, and the results show that the proposed reliability allocation method takes into account the transmission characteristics of the pipeline system and can improve the reliability of the gas transmission pipeline system with the minimum cost.

Citation Download Citation

Shiliang Peng, Huai Su, and Xiao Wang "Reliability allocation method for natural gas pipelines considering hydrothermal processes for pipeline natural gas transmission", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127842D (23 August 2023); https://doi.org/10.1117/12.3000040

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available