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A Harmonic Suppression Method Based on Fractional Lower Order Statistics for Power System

机译:基于分数低阶统计量的电力系统谐波抑制方法

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摘要

Impulse noise in power systems would seriously degrade the harmonic suppression performance. To remedy this problem, a novel harmonic suppression method based on fractional lower order statistics (FLOS) is proposed in this paper. In the proposed method, impulse noise is modeled by alpha-stable distribution. Then, the ESPRIT spectrum estimation algorithm is improved by FLOS for impulse noise and used to estimate the fundamental frequency of power signal, and the frequency of each harmonic component is obtained from this estimated frequency. Next, the amplitude of each harmonic component is estimated by a modified recursive least squares (RLS) algorithm. Finally, a harmonic compensation signal is generated by the active power filter based on the estimated frequencies and amplitudes to cancel original harmonics. The proposed method has a competitive advantage that it can suppress harmonics well even if the impulse noise activating and has a fast tracking ability for changing harmonics. Also, due to the use of self-sensing actuator principle, the proposed method can not only guarantee the performance of suppressing harmonics at normal operation states, but also ensure not to amplify harmonics in case of malfunction. The simulation results show that the proposed method has a better harmonic suppression performance than the existing ones under the impulse noise environment. The real experiments are also presented to verify the feasibility of the proposed method.
机译:电力系统中的脉冲噪声会严重降低谐波抑制性能。为了解决这个问题,本文提出了一种基于分数低阶统计量(FLOS)的谐波抑制方法。在所提出的方法中,通过α稳定分布来模拟脉冲噪声。然后,通过FLOS对脉冲噪声进行ESPRIT频谱估计算法的改进,并将其用于估计功率信号的基本频率,并从该估计频率中获得每个谐波分量的频率。接下来,通过改进的递归最小二乘(RLS)算法估算每个谐波分量的幅度。最后,有源功率滤波器根据估计的频率和幅度产生谐波补偿信号,以消除原始谐波。所提出的方法具有竞争优势,即使脉冲噪声被激活,它也可以很好地抑制谐波,并且具有用于改变谐波的快速跟踪能力。而且,由于使用了自感应致动器原理,所以所提出的方法不仅可以保证在正常工作状态下抑制谐波的性能,而且还可以确保在发生故障时不放大谐波。仿真结果表明,该方法在脉冲噪声环境下具有比现有方法更好的谐波抑制性能。还提出了真实的实验,以验证该方法的可行性。

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