基于改进Kaiser窗快速S变换和LightGBM的电能质量扰动识别与分类新方法  

A New Method for Identification and Classification of Power Quality Disturbance Based on Modified Kaiser Window Fast S-transform and LightGBM

作　　者：尹柏强[1] 陈奇彬 李兵[1] 佐磊[1] YIN Baiqiang;CHEN Qibin;LI Bing;ZUO Lei(National and Local Joint Engineering Laboratory for Renewable Energy Access to Grid Technology(Hefei University of Technology),Hefei 230009,Anhui Province,China)

机构地区：[1]可再生能源接入电网技术国家地方联合工程实验室(合肥工业大学),安徽省合肥市230009

出　　处：《中国电机工程学报》2021年第24期8372-8383,共12页Proceedings of the CSEE

基　　金：国家自然科学基金项目(61971175,51637004);国家重点研发计划“重大科学仪器设备开发”项目(2016YFF0102200);中央高校基本科研业务费项目(PA2021KCPY0037)。

摘　　要：针对S变换在电能质量扰动检测中存在计算量过大,时频分辨率低,电能质量扰动数据集常具备类别不平衡的问题,提出一种基于改进Kaiser窗快速S变换(modified Kaiser window fast S-transform,FMKST)和轻梯度提升机(light gradient boosting machine,LightGBM)的电能质量扰动识别与分类新方法。首先通过快速傅里叶变换得到采样信号频谱;然后利用迭代循环滤波区间定位算法确定扰动频率区间;再根据扰动频率区间所处频段确定窗宽调节因子并对相应区间进行变换;最后从采样信号的FMKST模时频矩阵中提取特征向量并构建改进LightGBM分类器进行分类。仿真与实验结果表明,提出的方法具有更高的识别准确率与更快的诊断速度,适用于海量电能质量扰动数据的快速识别与分类。Since the large amount of calculation and low time-frequency resolution of S-transform in power quality disturbance detection,and the power quality disturbance data sets often has the problem of unbalanced categories,a new method of power quality disturbance identification and classification based on modified Kaiser window fast S-transform(FMKST)and Light Gradient Boosting Machine(LightGBM)was proposed.Firstly,sampled signal spectrum was obtained through fast Fourier transform.Secondly,iterative loop filtering interval positioning algorithm was used to determine the disturbance frequency interval,and then the window parameters were determined according to the frequency range of the disturbance frequency interval and transform the corresponding interval;Finally,the feature vector was extracted from the FMKST modulus time-frequency matrix of the sampled signal and the modified LightGBM classifier was constructed for classification.Simulation and test results show that the proposed method has higher recognition accuracy and faster diagnosis speed,and is suitable for rapid identification and classification of massive power quality disturbance data.

关 键 词：电能质量 改进Kaiser窗 快速S变换 迭代循环滤波 LightGBM 

分 类 号：TM711[电气工程—电力系统及自动化]