Operational optimization of a cyclic gas pipeline network with consideration of thermal hydraulics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU143865" target="_blank" >RIV/00216305:26210/21:PU143865 - isvavai.cz</a>
Result on the web
<a href="https://pubs-acs-org.ezproxy.lib.vutbr.cz/doi/abs/10.1021/acs.iecr.0c04007" target="_blank" >https://pubs-acs-org.ezproxy.lib.vutbr.cz/doi/abs/10.1021/acs.iecr.0c04007</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1021/acs.iecr.0c04007" target="_blank" >10.1021/acs.iecr.0c04007</a>
Alternative languages
Result language
angličtina
Original language name
Operational optimization of a cyclic gas pipeline network with consideration of thermal hydraulics
Original language description
Following the rapidly increasing global demand for natural gas, many countries are launching projects to expand gas pipeline networks (GPNs). As a result, more cyclic GPNs are under construction with more rigorous physical constraints required, bringing new challenges to GPN optimization. This paper proposes a novel nonconvex mixed-integer nonlinear programming (MINLP) formulation for operational optimization of the cyclic GPN with simultaneous consideration of thermal hydraulics and flow direction reversibility, which has not been explored in the literature. To solve the proposed MINLP model, a three-level decomposition algorithm is proposed to generate an approximate solution, from which the flow direction is extracted and used to fix all discrete variables in the original MINLP model to construct two-stage NLP models. The NLP models are then solved to improve solution feasibility and quality. The computational results show that the proposed approach outweighs several state-of-the-art commercial MINLP solvers with better solutions and shorter computational time.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20704 - Energy and fuels
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
ISSN
0888-5885
e-ISSN
1520-5045
Volume of the periodical
6
Issue of the periodical within the volume
60
Country of publishing house
US - UNITED STATES
Number of pages
22
Pages from-to
2501-2522
UT code for WoS article
000621056900016
EID of the result in the Scopus database
2-s2.0-85101011602