程江洲,张志强,闫冉阳,李小来,谢卓然,胡哲豪
CHENG Jiangzhou,ZHANG Zhiqiang,YAN Ranyang,LI Xiaolai,XIE Zhuoran,HU Zhehao

• 1:三峡大学电气与新能源学院
• 2:国网山东省电力公司济宁供电公司
• 3:国网湖北超高压公司宜昌运维分部

摘要(Abstract)：

为实现对电网非平稳扰动信号的快速、准确分析，提出了融合SVD（奇异值分解）与ILMD（优化局部均值分解）的暂态电能质量扰动定位检测方法。首先，通过ILMD与模糊隶属度函数阈值处理噪声信息，削弱噪声干扰；然后，构造差值信号并利用滑窗SVD增强扰动特征，进一步抑制噪声干扰；最后，基于特征增强信号提出一种自适应阈值截断的暂态电能质量扰动定位检测方法。经仿真分析与算法对比，验证了所提方法定位准确、抗噪性强、计算量小，对过零与微弱扰动也有较好的定位效果。
Swiftly and accurately analyze non-stationary disturbance signals within the power grid, a location and detection method for transient power quality disturbance that combines singular value decomposition(SVD) and improved local mean decomposition(ILMD) is proposed. First, noise information is processed by using ILMD and a fuzzy membership function threshold to mitigate noise interference. Then, a difference signal is formulated, and a sliding window SVD is employed to amplify the disturbance features while further suppressing noise interference. In conclusion, an adaptive threshold truncation-based approach for localizing and detecting transient power quality disturbances is proposed, utilizing the feature-enhanced signal. Simulation analysis and algorithm comparisons confirm that the proposed method exhibits precise location, robust resistance to noise, and low computational complexity.Moreover, it demonstrates excellent performance in detecting zero-crossing and minor disturbances.

关键词(KeyWords)： 暂态电能质量;扰动定位检测;差值信号;奇异值分解;局部均值分解
transient power quality;disturbance location and detection;difference signal;SVD;LMD

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金（52277012）

作者(Author): 程江洲,张志强,闫冉阳,李小来,谢卓然,胡哲豪
CHENG Jiangzhou,ZHANG Zhiqiang,YAN Ranyang,LI Xiaolai,XIE Zhuoran,HU Zhehao

DOI: 10.19585/j.zjdl.202408001

参考文献(References)：

• [1]陈晓华，王志平，吴杰康，等.基于IHHO-SVM的电能质量扰动信号识别方法[J].浙江电力，2023,42(8):115-124.CHEN Xiaohua,WANG Zhiping,WU Jiekang,et al.Identification method for disturbance signal of power quality based on improve Harris Hawks optimization-support vector machine[J]. Zhejiang Electric Power,2023,42(8):115-124.
• [2]吴凯，施康明.基于SVD和PNN的电能质量扰动分析方法[J].浙江电力，2018,37(4):63-67.WU Kai,SHI Kangming.Analysis method of power quality disturbance based on SVD and PNN[J].Zhejiang Electric Power,2018,37(4):63-67.
• [3]谢小荣，贺静波，毛航银，等.“双高”电力系统稳定性的新问题及分类探讨[J].中国电机工程学报，2021,41(2):461-475.XIE Xiaorong,HE Jingbo,MAO Hangyin,et al.New issues and classification of power system stability with high shares of renewables and power electronics[J]. Proceedings of the CSEE,2021,41(2):461-475.
• [4]王燕.电能质量扰动检测的研究综述[J].电力系统保护与控制，2021,49(13):174-186.WANG Yan. Review of research development in power quality disturbance detection[J].Power System Protection and Control,2021,49(13):174-186.
• [5]董慧芬，陈蒙.电能质量信号的非均匀子带分解小波去噪[J].电子测量与仪器学报，2022,36(3):149-156.DONG Huifen,CHEN Meng. Wavelet de-noising of power quality signal based on non-uniform subband decomposition[J].Journal of Electronic Measurement and Instrumentation,2022,36(3):149-156.
• [6]龚静.可调阈值函数和能量阈值优化的电能质量扰动小波去噪方法[J].电子测量与仪器学报，2021,35(5):137-145.GONG Jing.Wavelet denoising method for power quality disturbances based on adjustable threshold function and energy threshold optimization[J].Journal of Electronic Measurement and Instrumentation,2021,35(5):137-145.
• [7]杨晓梅，郭朝云，樊博，等.采用奇异值梯度信息的暂态电能质量扰动自适应检测方法[J].电力自动化设备，2019,39(6):138-145.YANG Xiaomei,GUO Chaoyun,FAN Bo,et al.Adaptive detection method of transient power quality disturbance based on singular value gradient information[J]. Electric Power Automation Equipment,2019,39(6):138-145.
• [8]陈蓉，杨勇，樊明迪.新型电力系统下电能质量信号的分数域降噪方法研究[J].电测与仪表，2023,60(9):81-87.CHEN Rong,YANG Yong,FAN Mingdi. De-noising method of fractional domain for power quality signals in novel power system[J].Electrical Measurement&Instrumentation,2023,60(9):81-87.
• [9]李云峰，高云鹏，蔡星月，等.自适应辛几何模态分解和短时能量差分因子在电能质量扰动检测中的应用[J].电工技术学报，2022,37(17):4390-4400.LI Yunfeng,GAO Yunpeng,CAI Xingyue,et al.Application of adaptive symplectic geometry modal decomposition and short-time energy difference factor in power quality disturbance detection[J]. Transactions of China Electrotechnical Society,2022,37(17):4390-4400.
• [10]赵伟，袁至，王维庆，等.考虑电能质量优化的MMC-SST输入级控制策略[J].电力工程技术，2022,41(6):211-220.ZHAO Wei,YUAN Zhi,WANG Weiqing,et al. MMCSST input-level control strategy considering power quality optimization[J].Electric Power Engineering Technology,2022,41(6):211-220.
• [11]徐永海，赵燕.基于短时傅里叶变换的电能质量扰动识别与采用奇异值分解的扰动时间定位[J].电网技术，2011,35(8):174-180.XU Yonghai,ZHAO Yan. Identification of power quality disturbance based on short-term Fourier transform and disturbance time orientation by singular value decomposition[J].Power System Technology,2011,35(8):174-180.
• [12]廖晓辉，陈川川.一种改进的VMD-SVD电能质量扰动去噪新方法[J].水电能源科学，2021,39(4):190-194.LIAO Xiaohui,CHEN Chuanchuan.An improved VMDSVD power quality disturbance denoising method[J].Water Resources and Power,2021,39(4):190-194.
• [13]徐佳雄，张明，王阳，等.基于改进HHT的电能质量扰动检测新方法[J].智慧电力，2021,49(1):1-8.XU Jiaxiong,ZHANG Ming,WANG Yang,et al. New method of power quality disturbance detection based on improved HHT[J].Smart Power,2021,49(1):1-8.
• [14]王燕，李群湛，周福林.一种暂态电能质量扰动检测的新方法[J].中国电机工程学报，2017,37(24):7121-7132.WANG Yan,LI Qunzhan,ZHOU Fulin. A novel algorithm for transient power quality disturbances detection[J].Proceedings of the CSEE,2017,37(24):7121-7132.
• [15]宋海军，黄传金，刘宏超，等.基于改进LMD的电能质量扰动检测新方法[J].中国电机工程学报，2014,34(10):1700-1708.SONG Haijun,HUANG Chuanjin,LIU Hongchao,et al.A new power quality disturbance detection method based on the improved LMD[J]. Proceedings of the CSEE,2014,34(10):1700-1708.
• [16] LI Y B,LIANG X H,YANG Y T,et al.Early fault diagnosis of rotating machinery by combining differential rational spline-based LMD and K-L divergence[J].IEEE Transactions on Instrumentation and Measurement,2017,66(11):3077-3090
• [17] BASTOS A F,SANTOSO S. Universal waveshapebased disturbance detection in power quality data using similarity metrics[J].IEEE Transactions on Power Delivery,2020,35(4):1779-1787.