Intelligent Decision-Making Method and Software for Natural Gas Pipeline Operation Scheme
As the scale of natural gas pipelines expands and their operation becomes more complex, relying solely on the experience of field dispatchers to handle complex pipe network operation problems becomes increasingly challenging. To ensure safe and efficient operation, scientific decision-making software is crucial. In this paper, we combine the decision-making method based on the database (DMD) with the decision-making method based on optimization algorithm (DMOA) to establish an intelligent decision-making architecture for natural gas pipeline operation schemes. We also developed intelligent decision-making software for natural gas pipeline operation schemes (NGPOS-IDMS). According to normal and emergency conditions in the pipeline operation process, six decision modes are proposed based on database fuzzy query technology. Two types of pipeline operation optimization models were established for certain and uncertain gas supply scenarios, respectively. In order to verify the effectiveness of NGPOS-IDMS, China’s CD long-distance natural gas pipeline network was used as an example for analysis. The results show that only one optimal scheme can be obtained by DMOA, while the number of operation schemes generated by DMD is greater. Therefore, it is necessary to fully consider the advantages of both decision methods to provide decision support for field dispatchers.
Authors
- Jinghong Peng (ORCID: https://orcid.org/0000-0002-4071-509X)
- Can Qin (ORCID: https://orcid.org/0000-0003-0712-5378)
- Jun Zhou (ORCID: https://orcid.org/0000-0003-3230-6306)
- Tiantian Fu (ORCID: https://orcid.org/0000-0001-6175-9887)
- Chengyu Li (ORCID: https://orcid.org/0000-0002-4434-0838)
- Junjie Ma (ORCID: https://orcid.org/0009-0000-6678-5670)
- Zihao Xiong
- Sizhou Peng
- Guangchuan Liang
Institutions
- Sinopec (China) (CN)
- Southwest Petroleum University (CN)
Publication Details
- Journal
- Journal of Pipeline Systems Engineering and Practice
- Published
- 2025-02-20
- DOI
- https://doi.org/10.1061/jpsea2.pseng-1725
- Citations
- 1
- Primary Topic
- Integrated Energy Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.73