| 引用本文: | 吴建章,梅飞,潘益,周程,石天,郑建勇.基于改进经验小波变换的电能质量扰动检测新方法[J].电力自动化设备,2020,40(6): |
| WU Jianzhang,MEI Fei,PAN Yi,ZHOU Cheng,SHI Tian,ZHENG Jianyong.Novel detection method of power quality disturbance based on IEWT[J].Electric Power Automation Equipment,2020,40(6): |
|
| 摘要: |
| 针对经验小波变换(EWT)用于电能质量信号分析时，其频带划分结果易受频谱泄漏和噪声污染干扰的问题，提出一种基于改进经验小波变换(IEWT)的电能质量扰动检测新方法。首先，通过Fourier谱包络动态测度算法确定扰动信号的特征频点，并在原有频带边界的基础上进行延拓；然后，运用IEWT将扰动信号分解为若干调幅-调频(AM-FM)分量之和；最后对扰动分量实施标准希尔伯特变换，以求取扰动幅值、频率和起止时刻。通过算例仿真和变电站实测数据验证了所提方法的有效性，并对其检测结果进行对比分析。实验结果表明，所提方法兼具良好的模态分解能力和抗噪性能，且普适性更强，运算耗时更短，适用于工程实践。 |
| 关键词: 电能质量 扰动检测 改进经验小波变换 动态测度 标准希尔伯特变换 |
| DOI：10.16081/j.epae.202005014 |
| 分类号:TM761 |
| 基金项目:国家电网公司科技项目(52199918000C)；国家重点研发计划项目(2018YFB0905000) |
|
| Novel detection method of power quality disturbance based on IEWT |
|
WU Jianzhang1, MEI Fei2, PAN Yi1, ZHOU Cheng1, SHI Tian1, ZHENG Jianyong1
|
|
1.School of Electrical Engineering, Southeast University, Nanjing 210096, China;2.College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
|
| Abstract: |
| Aiming at the problem that the frequency band division result of EWT(Empirical Wavelet Trans-form) is susceptible to spectrum leakage and noise pollution when it is applied to power quality signal analysis, a novel method of power quality disturbance detection based on IEWT(Improved Empirical Wavelet Transform) is proposed. Firstly, the characteristic frequency points of the disturbance signal are determined by Fourier spectral envelope dynamic measurement algorithm, and the original frequency band boundaries are extended. Then the disturbance signal is decomposed into the sum of several AM-FM(Amplitude Modula-tion-Frequency Modulation) components by using IEWT. Finally, the normalized Hilbert transform is applied to the decomposition results to obtain the amplitude, frequency and start-stop time of disturbance. The validity of the proposed method is verified by numerical simulation and measured data of substation, and the results of the proposed method are compared with those of other methods. The experimental results show that the proposed method is more universal and easy to operate with good modal decomposition ability and anti-noise performance, and it is suitable for engineering practice. |
| Key words: power quality disturbance detection improved empirical wavelet transform dynamic measurement normalized Hilbert transform |
