Rapid low-frequency interharmonic detection with negative-frequency elimination

被引：0
作者：
School of Electrical Engineering & Information, Sichuan University, Chengdu [1 ]
610065, China
机构：
[1] School of Electrical Engineering & Information, Sichuan University, Chengdu
来源：
Dianli Zidonghua Shebei Electr. Power Autom. Equip. | / 3卷 / 140-145 and 156期
关键词：
Fast Fourier transforms; Harmonic analysis; Interharmonic; Negative-frequency; Rapid detection; Spectrum analysis; Ultralow-frequency interharmonic;
D O I：
10.16081/j.issn.1006-6047.2015.03.022
中图分类号：
学科分类号：
摘要：
The spectrum analysis of discrete power grid signal samples results in negative-frequency components, which interferes with the low-frequency interharmonic. When the frequency of interharmonic nears that of fundamental, harmonic or DC component, its spectrum will leak into the spectrum lines of the later and the generated main lobe interference will influence the accurate detection of interharmonic. A mathematical interharmonic model containing the negative-frequency is built and the influence of negative-frequency is eliminated by establishing and solving different spectrum line equations, based on which, the explicit formulas for calculating the low-frequency interharmonic parameters are obtained and the rapid low-frequency interharmonic detection satisfying the requirements of IEC standard for synchronous sampling is realized. The proposed method can rapidly and accurately detect the interharmonic based on a limited data length of samples, especially when the interval between the interharmonic and the near fundamental, harmonic or DC component is smaller than one frequency resolution. Simulative results show that, not affected by the DC offset and harmonic components, it has better detection speed and noise immunity. ©, 2015, Electric Power Automation Equipment Press. All right reserved.
引用
收藏
页码：140 / 145and156
相关论文
共 17 条
  • [1] IEC61000-4-7 General guide on harmonics and interharmonics measurements, for power supply systems and equipment connected thereto, (2009)
  • [2] Huang C., Cao W., Chen T., Et al., Application of local mean decomposition in power quality disturbance detection, Electric Power Automation Equipment, 33, 9, pp. 68-73, (2013)
  • [3] Wang J., Liu H., Liu C., Identification of harmonic and interharmonic sources based on composite criterion, Electric Power Automation Equipment, 33, 7, pp. 63-69, (2013)
  • [4] Chen G., Chen L., Cai Z., Harmonic analysis based on Nuttall window interpolation FFT, Electric Power Automation Equipment, 31, 4, pp. 27-31, (2011)
  • [5] Mao Y., Tu Y., Xiao W., Et al., Advances and trends of study on discrete intensive frequency spectrum zooming analysis and correction methodology, Journal of Vibration and Shock, 31, 21, pp. 112-119, (2012)
  • [6] Shi M., Wu Z., Yin W., Inter-harmonic parameter estimation based on multi-signal classification and Prony method, Power System Technology, 29, 15, pp. 81-84, (2005)
  • [7] Zhang Y., He J., Li T., Et al., A new method to detect harmonics and inter-harmonics based on mathematical morphology and Hilbert-Huang transform, Power System Technology, 32, 17, pp. 46-51, (2008)
  • [8] Hou L., Huang C., Li B., Et al., Harmonic and interharmonic measurement methods based on Chinese national standard and IEC standard, Power System Technology, 34, 8, pp. 46-51, (2010)
  • [9] Jin W., Liu H., An optimal method for harmonics and interharmonics measurement in the IEC standard framework, Automation of Electric Power Systems, 36, 2, pp. 70-76, (2012)
  • [10] Zhang B., Yu L., He J., Et al., Inter-harmonic detection based on fast TLS-ESPRIT, Electric Power Automation Equipment, 31, 2, pp. 26-31, (2011)
12