A Verification Method for a Bay Configuration File of Intelligent Substation Renovation and Expansion in Power Systems
New renovation and expansion projects of intelligent substations may cause frequent changes in the internal configuration of intelligent electronic devices, making it difficult for on-site inspection personnel to verify their configuration files. Therefore, this paper proposes an intelligent substation renovation and expansion project bay configuration file verification method based on cyclic redundancy check dynamic verification. Firstly, the logical relationship of configuration description files involved in the renovation and expansion project was introduced in detail, and bay decoupling and secondary circuit identification techniques were used to assign secondary equipment to bays. Then, the cyclic redundancy check dynamic verification method is introduced for the online diagnosis of configuration files and to manage and locate the secondary circuits associated with the bay of the renovation and expansion project. Finally, the semantic recognition method was used to verify the correctness of the virtual circuit configuration information. The effectiveness of the method was verified using a 220 kV substation in the Heilongjiang power grid as an example, which can effectively meet the application needs of intelligent substation renovation and expansion projects.
Authors
- Mingxu Hu (ORCID: https://orcid.org/0000-0003-3603-3966)
- Wei Yang (ORCID: https://orcid.org/0000-0001-5854-7568)
- Peiyong Yu (ORCID: https://orcid.org/0000-0001-5279-0479)
- Hao Wang (ORCID: https://orcid.org/0000-0003-3568-3350)
- Di Lu (ORCID: https://orcid.org/0000-0002-3054-6325)
- Hongbo Zou (ORCID: https://orcid.org/0000-0002-5880-8163)
- Shi Ru
Institutions
- China Three Gorges University (CN)
- Harbin Electric Corporation (China) (CN)
Publication Details
- Journal
- Processes
- Published
- 2025-10-14
- DOI
- https://doi.org/10.3390/pr13103273
- Citations
- 1
- Primary Topic
- Power Systems and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.73