电力系统保护与控制2026，Vol.54Issue(7)：80-91,12.DOI:10.19783/j.cnki.pspc.250867
适用于新能源电力系统交流线路过流保护在线整定的高效极端运行方式搜索方法
Efficient extreme operating condition search method for online relay setting of overcurrent protection for AC transmission lines in new energy power systems
摘要
Abstract
Extreme operating condition search(EOCS)is one of the core issues in relay protection setting calculation,used to ensure that protection settings can adapt to variations in system operating conditions over a certain period after being deployed.In new energy power systems,operating conditions are more flexible and dynamic,necessitating online setting calculation methods.However,existing EOCS methods fail to meet the efficiency requirements of online applications.To reduce computation time,this paper applies deep learning to the EOCS problem for the first time and proposes an efficient method based on a parallel graph neural network.First,the power system structure is modeled using four matrices,and feature extraction is performed by a graph neural network.Subsequently,the high-dimensional features are concatenated and flattened before being fed into a decision network to predict extreme operating conditions.Finally,the proposed method is validated on the IEEE39-bus and 118-bus systems.Results demonstrate that the proposed method achieves higher accuracy while significantly improving computational efficiency.关键词
极端运行方式搜索/图神经网络/新能源电力系统/整定计算Key words
extreme operating condition search/graph neural network/new energy power system/setting calculation引用本文复制引用
李彦,杨增力,王晶,王紫薇,韩笑宇,王镜毓,李银红,石东源..适用于新能源电力系统交流线路过流保护在线整定的高效极端运行方式搜索方法[J].电力系统保护与控制,2026,54(7):80-91,12.基金项目
This work is supported by the National Natural Science Foundation of China(No.52207107). 国家自然科学基金项目资助(52207107) （No.52207107）
中国科协青年人才托举工程项目资助(YESS20240100) （YESS20240100）
