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This paper proposes a solution for the verification function of substation monitoring system upgrades based on secondary equipment in substations. By utilizing technologies such as data stabilization for smooth system upgrades, rapid verification of data and functions after system upgrades, and comprehensive main-substation simulation models tailored to upgrade validation requirements, the solution enhances both the efficiency and consistency of substation equipment upgrades. It also ensures the stability and security of the monitoring system upgrades. Verification and analysis indicate that the proposed verification function for substation monitoring system upgrades is stable and reliable, providing effective support for upgrade validations of older substations. This approach significantly improves the accuracy of system and equipment data and the correctness of functionality after upgrades. a deep learning analysis of online monitoring information of substation secondary equipment was carried out to identify and resolve potential issues before the on-site debugging phase in technical renovation projects, thereby shortening the construction timeline for upgrades of older substations. The construction period of the substation is greatly shortened.

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Design and Development of Upgrade Verification Function for Plant Monitoring System Based on Substation Secondary Equipment

  • 会议论文

  • 发表日期：

    2025年

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  • Liang Lv,
  • Yulong Pei,
  • Hualiang Zhou,
  • Xuan Wang,
  • Yi Huang,
  • Kui Lin,
  • Chuanyu Zhang,
  • Rui Zhang,
  • Wei Han,
  • YuanYuan Li

摘要

This paper proposes a solution for the verification function of substation monitoring system upgrades based on secondary equipment in substations. By utilizing technologies such as data stabilization for smooth system upgrades, rapid verification of data and functions after system upgrades, and comprehensive main-substation simulation models tailored to upgrade validation requirements, the solution enhances both the efficiency and consistency of substation equipment upgrades. It also ensures the stability and security of the monitoring system upgrades. Verification and analysis indicate that the proposed verification function for substation monitoring system upgrades is stable and reliable, providing effective support for upgrade validations of older substations. This approach significantly improves the accuracy of system and equipment data and the correctness of functionality after upgrades. a deep learning analysis of online monitoring information of substation secondary equipment was carried out to identify and resolve potential issues before the on-site debugging phase in technical renovation projects, thereby shortening the construction timeline for upgrades of older substations. The construction period of the substation is greatly shortened.