TITLE:
A Tunable Resolution MUSIC Algorithm for Interharmonics Analysis
AUTHORS:
Ming Zhang, Xiang Zhang, Heng Yao, Shunfan He
KEYWORDS:
Interharmonics Analysis, Tunable Resolution Multiple Signal Classification (TRMUSIC) Algorithm, Subspace Decomposition, Spectral Analysis
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.5 No.9,
August
31,
2017
ABSTRACT: The harmonic and interharmonic analysis recommendations are contained in the latest IEC standards on power quality. Measurement and analysis experiences have shown that great difficulties arise in the interharmonic detection and measurement with acceptable levels of accuracy. In order to improve the resolution of spectrum analysis, the traditional method (e.g. discrete Fourier transform) is to take more sampling cycles, e.g. 10 sampling cycles corresponding to the spectrum interval of 5 Hz while the fundamental frequency is 50 Hz. However, this method is not suitable to the interharmonic measurement, because the frequencies of interharmonic components are non-integer multiples of the fundamental frequency, which makes the measurement additionally difficult. In this paper, the tunable resolution multiple signal classification (TRMUSIC) algorithm is presented, which the spectrum can be tuned to exhibit high resolution in targeted regions. Some simulation examples show that the resolution for two adjacent frequency components is usually sufficient to measure interharmonics in power systems with acceptable computation time. The proposed method is also suited to analyze interharmonics when there exists an undesirable asynchronous deviation and additive white noise.