基于实值MUSIC算法的电力谐波分析方法

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (374 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract In recent years, modern spectral estimation methods, especially the MUSIC (Multiple Signal Classification) algorithms, are gradually used for high-resolution power harmonic analysis. However, most of them are proposed to detect frequencies of complex signals so that any real-valued signal should be transformed into complex form. The preprocessing may lead to higher computation burden. In addition to this, the picket-fence effect also exists in searching spectrum peaks, which causes low analyzing precision. To overcome these drawbacks, a real-valued MUSIC algorithm for power harmonic analysis is proposed in the paper based on subspace decomposition theory. And the computing method of pseduospectra is also derived. Furthermore, to improve the measuring accuracy of harmonics, Newton-Raphson algorithm is adopted to optimize the harmonic frequencies significantly. Simulation results show that: the spectral peaks of true harmonic components are more distinct from false peaks caused by noise in the real-valued MUSIC, and the computational complexity is notably lower than that of the classic MUSIC, as well as the detecting precision is close to that of root-MUSIC algorithm which is quite time-consuming.

Key words： Power harmonic analysis modern spectral estimation method MUSIC algorithm subspace decomposition Newton-Raphson optimization

Received: 18 December 2008 Published: 18 February 2014

PACS:	TM711
	TM415

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Cai Tao
	Duan Shanxu
	Liu Fangrui

Cite this article:

Cai Tao,Duan Shanxu,Liu Fangrui. Power Harmonic Analysis Based on Real-Valued Spectral MUSIC Algorithm[J]. Transactions of China Electrotechnical Society, 2009, 24(12): 149-155.

URL:

http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2009/V24/I12/149

[1] Carbone R, Testa A, Menniti D, et al. Harmonic and interharmonics distortion in current source type inverter drives[J]. IEEE Transactions on Power Delivery, 1995, 10(3): 1576-1583.
[2] Zhang F S, Geng Z X, Yuan W. The algorithm of interpolating windowed FFT for harmonic analysis of power system[J]. IEEE Transactions on Power Delivery, 2001, 16(2): 160-164.
[3] 赵文春, 马伟明, 胡安. 电机测试中谐波分析的高精度FFT算法[J].中国电机工程学报. 2001, 21(12): 83-87.
[4] 薛蕙, 杨仁刚. 基于Morlet连续小波变换的非整数次谐波测量方法[J]. 电网技术, 2002, 26(12): 41-44.
[5] Pham V L, Wong K P. Wavelet-transform-based algorithm for harmonic analysis of power system waveforms[J]. IEE Proceeding of Generation, Trans- mission and Distribution, 1999, 146(3): 249-254.
[6] Leonowicz Z, Lobos T, Rezmer J. Advanced spectrum estimation methods for signal analysis in power electronics[J]. IEEE Transactions on Industrial Electronics, 2003, 50 (3): 514-519.
[7] 丁屹峰, 程浩忠, 吕干云, 等.基于 Prony 算法的谐波和间谐波频谱估计[J]. 电工技术学报, 2005, 20(10): 94-97.
[8] Zhan Yong, Cheng Haozhong. A robust support vector algorithm for harmonic and interharmonic analysis of electric power system[J]. Electric Power Systems Research, 2005, 73(3): 393-400.
[9] Lobos T, Leonowicz Z, Rezmer J, et al. High- resolution spectrum-estimation methods for signal analysis in power systems[J]. IEEE Transactions on Instrumentation and Measurement, 2006, 55(1): 219- 225.
[10] 高培生, 谷湘文, 吴为麟. 基于求根多重信号分类和遗传算法的谐波间谐波频谱估计[J]. 电工技术学报, 2008, 23(6): 109-113.
[11] 石敏, 吴正国, 尹为民. 基于多信号分类法和普罗尼法的间谐波参数估计[J]. 电网技术, 2005, 29(1): 81-84.
[12] Schmidt R O. Multiple emitter location and signal parameter estimation[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276-280.
[13] Bhashar D R, Hari K V S. Performance analysis of root-MUSIC[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1989, 37(12): 1939- 1949.