Electric Power ›› 2026, Vol. 59 ›› Issue (6): 37-47.DOI: 10.11930/j.issn.1004-9649.202510087

• Intelligence, Green, Resilience: Technology and Market Integration for the New Electricity System Toward 2035 • Previous Articles     Next Articles

Intelligent substation model conversion method based on multi-dimensional similarity optimization and XSLT

SHI Hengchu1(), YANG Qiaowei1, YOU Hao1, XU Shoudong2, CHEN Xiaofan1, HU Xiao1   

  1. 1. Yunnan Power Grid Co., Ltd., Kunming 650011, China
    2. Electric Power Research Institute of Yunnan Power Grid Co., Ltd., Kunming 650217, China
  • Received:2025-10-29 Revised:2026-03-20 Online:2026-06-22 Published:2026-06-28
  • Supported by:
    This work is supported by National Natural Science Foundation of China (No.52077120), and Science and Technology Project of Yunnan Power Grid Co., Ltd. (No.YNKJXM20240220).

Abstract:

In order to meet the higher requirements of information interconnection put forward by the in-depth construction of intelligent substations, it has become a key bottleneck in the development of intelligent substations to solve the heterogeneous problem of IEC 61850 substation configuration description (SCD) models caused by the differentiation of technical routes and topological configurations of equipment manufacturers. In order to solve the problem of semantic conflict and inefficient transformation, a model transformation method based on multi-dimensional similarity optimization and extensible style sheet language transformations (XSLT) is proposed. Firstly, the ontology parsing of the common information model (CIM) model is realized through the co-mapping of unified modeling language (UML) and web ontology language (OWL). Furthermore, a node similarity calculation model combining syntactic, semantic and structural three-dimensional features is proposed, and the F-value optimization is introduced to determine the optimal weight and matching threshold, so as to realize the accurate mapping from CIM to IEC 61850 model. Finally, the XSLT script is automatically generated based on the mapping relationship, and the automatic conversion and semantic adaptation of the SCD file are completed by combining the Dom4j tool library. The simulation results show that the proposed method takes only 3.2 seconds to convert under the premise of completely retaining the source model equipment and topology information, and the efficiency is increased by more than 96% compared with the manual method, and provide reliable technical support for the multi-level integration of intelligent substations and the coordinated operation of the power grid.

Key words: intelligent substation, public information model, heterogeneous model mapping