Research on distribution network fault processing technology based on knowledge of graph

Author:

Li QiangORCID,Zhao Feng,Zhuang Li,Su Jiangwen,Zhang Xiaodong

Abstract

Safety and reliability are the basis of the development of a distribution network. To analyze the risk transmission process in the distribution network and ensure the safe and reliable operation of the power system, this paper intends to use the knowledge graph method to realize the risk analysis of the distribution network information system. Firstly, the knowledge graph method is used to extract and integrate the risk knowledge of the multi-dimensional information collected by the distribution network. Secondly, the knowledge graph model of distribution network risk analysis is constructed, and the multi-dimensional distribution network fault handling and knowledge graph construction oriented to the feeder and platform area are designed. The distribution line parameters of the low-voltage distribution network model, neutral point grounding mode, and different fault types are analyzed, and the non-planned island is searched based on the knowledge graph adjacency matrix. Finally, combined with the simulation experiment, it is verified that the proposed method can effectively depict the information risk process of the distribution network. The structure of this paper starts from the multi-node complex distribution network, combined with a knowledge graph and deep learning method, which can solve the distribution network fault more quickly.

Funder

two-level collaborative R&D project of State Grid Information and Communication Industry Group

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference30 articles.

1. A multi-agent-based symbiotic organism search algorithm for DG coordination in electrical distribution networks[J];Kawambwa Shamte;Journal of Electrical Systems and Information Technology,2023

2. Multilevel optimization of economic dispatching in active distribution network based on ADMM[J].;Qi Jun;Frontiers in Energy Research,2023

3. Integration of solar-based charging stations in the power distribution network and charging scheduling of EVs[J].;Shafiq Aqib;Frontiers in Energy Research,2023

4. Modeling synthetic power distribution network and datasets with industrial validation[J];M. Ali;Journal of Industrial Information Integration,2023

5. Feasibility assessment of net-zero-energy transformation of building stock using integrated synthetic population, building stock, and power distribution network framework[J].;Yamaguchi Yohei;Applied Energy,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3