Open AccessHarmonic separation from grid voltage using ensemble empirical‐mode decomposition and independent component analysis
Author(s) -
Cai Kewei,
Wang Zhiqiang,
Li Guofeng,
He Donggang,
Song Jinyan
Publication year - 2017
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2405
Subject(s) - harmonic , harmonics , hilbert–huang transform , computer science , blind signal separation , independent component analysis , electronic engineering , source separation , grid , harmonic analysis , noise (video) , voltage , algorithm , channel (broadcasting) , engineering , mathematics , electrical engineering , artificial intelligence , acoustics , white noise , telecommunications , physics , geometry , image (mathematics)
Summary Harmonics and subharmonics in power systems distort grid voltage, reduce the quality of power, and affect the security of the power grid. Rapid and accurate harmonic separation from grid voltage is the crucial technology to ensure that power systems operate safely and stably. The blind source separation method based on independent component analysis has been used to separate the components of grid voltage. As the grid voltage is acquired in only a single channel, harmonic separation from it is classed as a single‐channel independent component analysis problem. Hence, this paper proposes a method for the harmonic separation of single‐channel grid voltage that combines ensemble empirical‐mode decomposition and FastICA. Compared with 2 traditional methods, the fast Fourier transform and the discrete wavelet transform, the proposed method is superior in that it does not require prior knowledge of the frequency of the original source, does not feature mode mixing, and is more robust against noise. Results obtained from both synthetic and real‐life signals demonstrated the excellent performance of the proposed method.