Systematic modeling and methodological approaches for optimizing gas storage facility design with fluctuating hydraulic characteristics

As the proportion of natural gas consumption in the energy market gradually increases, optimizing the design of gas storage surface system (GSSS) has become a current research focus. Existing studies on the two independent injection pipeline network (InNET) and production pipeline network (ProNET) f...

Full description

Saved in:
Bibliographic Details
Published in:Petroleum science Vol. 22; no. 6; pp. 2546 - 2569
Main Authors: Liu, Shi-Tao, Li, Cheng-Yu, Zhou, Jun, Li, Zi-Chen, Ye, Zhan-Peng, Peng, Jing-Hong, Zhao, Yun-Xiang, Liang, Guang-Chuan
Format: Journal Article
Language:English
Published: Beijing Elsevier B.V 01.06.2025
KeAi Publishing Communications Ltd
Subjects:
Algorithms
Boundaries
Design
Design optimization
Design parameters
Energy consumption
Gas pipelines
Gas storage
Genetic algorithms
Hybrid genetic algorithm based on generalized reduced gradient
Hydraulic characteristics
Hydraulics
Injection
Multi-condition
Natural gas
Parameters
Pipeline diameter optimization
Pressure
Sensitivity analysis
Simulation
Storage facilities
Underground storage
China
Gas storage
Hybrid genetic algorithm based on generalized reduced gradient
Hydraulic characteristics
Pipeline diameter optimization
Multi-condition
ISSN:1995-8226, 1672-5107, 1995-8226
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:As the proportion of natural gas consumption in the energy market gradually increases, optimizing the design of gas storage surface system (GSSS) has become a current research focus. Existing studies on the two independent injection pipeline network (InNET) and production pipeline network (ProNET) for underground natural gas storage (UNGS) are scarce, and no optimization methods have been proposed yet. Therefore, this paper focuses on the flow and pressure boundary characteristics of the GSSS. It constructs systematic models, including the injection multi-condition coupled model (INM model), production multi-condition coupled model (PRM model), injection single condition model (INS model) and production single condition model (PRS model) to optimize the design parameters. Additionally, this paper proposes a hybrid genetic algorithm based on generalized reduced gradient (HGA-GRG) for solving the models. The models and algorithm are applied to a case study with the objective of minimizing the cost of the pipeline network. For the GSSS, nine different condition scenarios are considered, and iterative process analysis and sensitivity analysis of these scenarios are conducted. Moreover, simulation scenarios are set up to verify the applicability of different scenarios to the boundaries. The research results show that the cost of the InNET considering the coupled pressure boundary is 64.4890 × 104 CNY, and the cost of the ProNET considering coupled flow and pressure boundaries is 87.7655 × 104 CNY, demonstrating greater applicability and economy than those considering only one or two types of conditions. The algorithms and models proposed in this paper provide an effective means for the design of parameters for GSSS.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1995-8226
1672-5107
1995-8226
DOI:10.1016/j.petsci.2025.04.009