Current trajectory image-based protection algorithm for transmission lines connected to MMC-HVDC stations using CA-CNN

作     者：Yingyu Liang Yi Ren Jinhua Yu Wenting Zha 

作者机构：School of Mechanical Electronic and Information EngineeringChina University of Mining and Technology(Beijing)Beijing 100083China 

出 版 物：《Protection and Control of Modern Power Systems》 (现代电力系统保护与控制（英文）)

年 卷 期：2023年第8卷第1期

页      面：97-111页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported in part by the Fundamental Research Funds for the Central Universities under Grant 2022JCCXJD01 in part by Training Program of Innovation and Entrepreneurship for Undergraduates of China University of Mining and Technology(Beijing)under Grant 202204009 

主　　题：Channel attention mechanism Convolutional neural network(CNN) Differential current Current trajectory image Modular multilevel converter-based high voltage direct current(MMC-HVDC) 

摘      要：In the presence of an MMC-HVDC system,current differential protection(CDP)has the risk of failure in operation under an internal *** addition,CDP may also incur security issues in the presence of current transformer(CT)saturation and *** this paper,a current trajectory image-based protection algorithm is proposed for AC lines connected to MMC-HVDC stations using a convolution neural network improved by a channel attention mechanism(CA-CNN).Taking the dual differential currents as two-dimensional coordinates of the moving point,the moving-point trajectories formed by differential currents have significant differences under internal and external ***,internal faults can be identified using image recognition based on *** is improved by a channel attention mechanism,data augmentation,and adaptive learning *** comparison with other machine learning algorithms,the feature extraction ability and accuracy of CA-CNN are greatly *** fault conditions like different net-work structures,operation modes,fault resistances,outliers,and current transformer saturation,are fully considered to verify the superiority of the proposed protection *** results confirm that the proposed current trajectory image-based protection algorithm has strong learning and generalizability,and can identify internal faults reliably.