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

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.