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Harmonic separation from grid voltage using ensemble empiricalmode decomposition and independent component analysis

机译:集成经验模态分解和独立分量分析与电网电压谐波分离

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摘要

Harmonics and subharmonics in power systems distort grid voltage, reduce the qualityrnof power, and affect the security of the power grid. Rapid and accurate harmonicrnseparation from grid voltage is the crucial technology to ensure that power systemsrnoperate safely and stably. The blind source separation method based on independentrncomponent analysis has been used to separate the components of grid voltage. Asrnthe grid voltage is acquired in only a single channel, harmonic separation from itrnis classed as a single‐channel independent component analysis problem. Hence, thisrnpaper proposes a method for the harmonic separation of single‐channel grid voltagernthat combines ensemble empirical‐mode decomposition and FastICA. Comparedrnwith 2 traditional methods, the fast Fourier transform and the discrete waveletrntransform, the proposed method is superior in that it does not require priorrnknowledge of the frequency of the original source, does not feature mode mixing,rnand is more robust against noise. Results obtained from both synthetic and real‐lifernsignals demonstrated the excellent performance of the proposed method.
机译:电力系统中的谐波和次谐波会扭曲电网电压,降低电能质量,并影响电网的安全性。从电网电压中快速准确地分离谐波是确保电力系统安全稳定运行的关键技术。基于独立分量分析的盲源分离方法已被用于分离电网电压的分量。电网电压仅在单个通道中获得,与itrnis的谐波分离被归类为单通道独立分量分析问题。因此,本文提出了一种结合整体经验模态分解和FastICA的单通道电网电压谐波分离方法。与快速傅里叶变换和离散小波变换这两种传统方法相比,该方法具有优越性,不需要先验原始信号源的频率,不具有模式混合特性,对噪声更鲁棒。从合成信号和真实信号获得的结果证明了该方法的出色性能。

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