Construction and application of knowledge graph for grid dispatch fault handling based on pre-trained model

• Published in: Global Energy Interconnection Vol. 6; no. 4; pp. 493 - 504
• Main Authors: Ji, Zhixiang, Wang, Xiaohui, Zhang, Jie, Wu, Di
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2023
• Subjects: Auxiliary decision-making; Knowledge graph; Power-grid dispatch fault handling; Pre-trained model; Power-grid dispatch fault handling; Auxiliary decision-making; Pre-trained model; Knowledge graph
• ISSN: 2096-5117
• DOI: 10.1016/j.gloei.2023.08.009

With the construction of new power systems, the power grid has become extremely large, with an increasing proportion of new energy and AC/DC hybrid connections. The dynamic characteristics and fault patterns of the power grid are complex; additionally, power grid control is difficult, operation risks are high, and the task of fault handling is arduous. Traditional power-grid fault handling relies primarily on human experience. The difference in and lack of knowledge reserve of control personnel restrict the accuracy and timeliness of fault handling. Therefore, this mode of operation is no longer suitable for the requirements of new systems. Based on the multi-source heterogeneous data of power grid dispatch, this paper proposes a joint entity–relationship extraction method for power-grid dispatch fault processing based on a pre-trained model, constructs a knowledge graph of power-grid dispatch fault processing and designs, and develops a fault-processing auxiliary decision-making system based on the knowledge graph. It was applied to study a provincial dispatch control center, and it effectively improved the accident processing ability and intelligent level of accident management and control of the power grid.