全球能源互联网（英文）2023，Vol.6Issue(1)：15-25,11.DOI:10.1016/j.gloei.2023.02.002
面向配用电网运行数据相似性匹配的神经信息检索技术研究
Similarity matching method of power distribution system operating data based on neural information retrieval
摘要
Abstract
Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy. Therefore, improvement of the ability of data-driven operation management, intelligent analysis, and mining is urgently required. To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation, maintenance experience, and knowledge by rule and line, a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology. Based on the processing flow of the operating data of the power distribution system, a technical framework of neural information retrieval is established. Combined with the natural graph characteristics of the power distribution system, a unified graph data structure and a data fusion method of data access, data complement, and multi-source data are constructed. Further, a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed. The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set. The model is verified on the operating section of the power distribution system of a provincial grid area. The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.关键词
神经信息检索/配用电/图数据/图嵌入/相似性匹配Key words
Neural information retrieval/Power distribution/Graph data/Operating section/Similarity matching引用本文复制引用
肖凯,李道兴,郭鹏天,王晓辉,陈勇..面向配用电网运行数据相似性匹配的神经信息检索技术研究[J].全球能源互联网（英文）,2023,6(1):15-25,11.基金项目
This study was supported by the National Key R&D Program of China(2020YFB0905900). （2020YFB0905900）
