Publication detail

Operational optimization of a cyclic gas pipeline network with consideration of thermal hydraulics

Zheng, T. Feng, H. Wang, B. Zheng, J. Liang, Y. Ma, Y. Keene, T. Li, J.

English title

Operational optimization of a cyclic gas pipeline network with consideration of thermal hydraulics

Type

journal article in Web of Science

Language

en

Original abstract

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.

English abstract

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.

Keywords in English

operational; optimization; cyclic; gas; pipeline; network; consideration; thermal; hydraulics

Released

17.02.2021

Publisher

American Chemical Society

ISSN

0888-5885

Volume

6

Number

60

Pages from–to

2501–2522

Pages count

22

BIBTEX


@article{BUT177024,
  author="Bohong {Wang},
  title="Operational optimization of a cyclic gas pipeline network with consideration of thermal hydraulics",
  year="2021",
  volume="6",
  number="60",
  month="February",
  pages="2501--2522",
  publisher="American Chemical Society",
  issn="0888-5885"
}