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    李国锋

    • 教授     博士生导师   硕士生导师
    • 性别:男
    • 毕业院校:大连理工大学
    • 学位:博士
    • 所在单位:电气工程学院
    • 学科:电工理论与新技术
    • 办公地点:A3区32号楼静电与特种电源研究所201室
    • 联系方式:+86-411-84706489(O)
    • 电子邮箱:guofenli@dlut.edu.cn

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    Harmonic separation from grid voltage using ensemble empirical-mode decomposition and independent component analysis

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    论文类型:期刊论文

    第一作者:Cai, Kewei

    通讯作者:Wang, ZQ (reprint author), Dalian Univ Technol, Sch Elect Engn, 2 Linggong Rd, Dalian, Peoples R China.

    合写作者:Wang, Zhiqiang,Li, Guofeng,He, Donggang,Song, Jinyan

    发表时间:2017-11-01

    发表刊物:INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS

    收录刊物:SCIE、EI

    卷号:27

    期号:11

    ISSN号:2050-7038

    关键字:blind source separation; empirical-mode decomposition; harmonics; independent component analysis; single-channel ICA; subharmonics

    摘要: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.