基于逻辑回归的直流串联电弧故障检测算法与设计  

Algorithm and Design of DC Series Arc Fault Detection Based on Logistic Regression Method

作　　者：黄亦凡 罗利文[1] Huang Yifan;Luo Liwen(School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《电气自动化》2024年第4期53-55,59,共4页Electrical Automation

摘　　要：针对光伏系统中直流串联电弧故障,搭建了直流电弧试验平台。利用霍尔电流传感器获得大量故障电流数据,从数据的时频域中提取了四个能反映电流与电弧故障关系的特征量;提出一种计算特征量变化量的方法,有效避免了传统固定阈值比较法难以适用于复杂多样工况的问题;利用机器学习逻辑回归方法,得到电弧故障的检测参数,通过大量数据验证,发现几乎不会有电弧错报情况。所提算法能够运用于嵌入式设备并部署在光伏系统用于电弧检测。A DC arc test platform was established to address DC series arc faults in photovoltaic systems.Using Hall current sensors to obtain a large amount of fault current data,four characteristic quantities that can reflect the relationship between current and arc faults were extracted from the time-frequency domain of the data;a method for calculating the variation of feature quantities was proposed,effectively avoiding the problem of traditional fixed threshold comparison methods being difficult to apply to complex and diverse working conditions;by using machine learning logistic regression methods,the detection parameters for arc faults were obtained.Through extensive data validation,it was found that there were almost no arc false alarms.The proposed algorithm can be applied to embedded devices and deployed in photovoltaic systems for arc detection.

关 键 词：直流串联电弧故障 逻辑回归 霍尔电流传感器 光伏系统 快速傅里叶变换 

分 类 号：TM914[电气工程—电力电子与电力传动]