Electric Power ›› 2026, Vol. 59 ›› Issue (1): 57-65.DOI: 10.11930/j.issn.1004-9649.202506055

• Energy and Electricity Data Elements and Artificial Intelligence Applications • Previous Articles     Next Articles

The machine-recognition technology path of standard digital transformation in the field of smart energy

LI Wenwen(), LIYAN Ruoyue   

  1. National institute of metrology China, Beijing 100029, China
  • Received:2025-06-19 Revised:2025-12-23 Online:2026-01-13 Published:2026-01-28
  • Supported by:
    This work is supported by the National Key Research and Development Program of China (No.2021YFF0601400).

Abstract:

Smart energy is one of the most important directions of energy revolution and transformation. Its standardization can provide strong support for technology advancement and industrial development in energy field. In the context of the overarching trend of digital development, the digital transformation of standards has also become an inevitable trend. This paper conducted research on machine-recognition technology pathways for the digital transformation of standards in the field of smart energy. A pathway was established, which includes the development of a general standard information model, the creation of extensible label set mapping rules, standard format conversion, verification and evaluation using the verification tool, and standard optimization feedback. Four international standards of smart energy were selected for practical implementation. The transformation and validation of the identifiable levels of these four standards were completed, and the maturity and applicability of the identifiable levels were evaluated. The results show that the maturity and applicability of the identifiable levels of the four standards are high. This study provides a feasible technology pathway for the initial stage of digital transformation of standards in the smart energy field and serves as an important reference for standard digitalization research and practice in related fields.

Key words: smart energy, standard, digitization, machine-recognition