Analysis of μPMU Noise Characteristics and Its Influence on Distribution Network Fault Location

The application of Micro Phasor Measurement Unit (μPMU) provides a new technological approach for distribution network fault location. In order to improve the accuracy and reliability of fault location, the study of the characteristics for μPMU noise and its impact on fault location algorithms is of necessity. This paper proposed a PMU measurement error model for noise characteristics analysis. And the noise was introduced into the system to examine its effect on the traditional impedance fault location method. To analyze the noise characteristics, a median filter was used to extract the μPMU noise from the raw data. The Monte Carlo method was used to obtain the sample of the fault location error under the influence of μPMU noise. The observed data was fitted with the Gaussian Mixture Model (GMM) then evaluated by the goodness-of-fit (GOF) indexes in regression analysis theory. This method is used on both μPMU noise characteristics analysis and the fault location error under the influence of μPMU noise. The conclusion was reached: μPMU noise and the location error both obey the Gaussian distribution and the result was validated by actual μPMU measured data. The result of fault location error with μPMU noise is presented. The result shows that the accuracy of the impedance method is greatly influenced by the μPMU noise, and the accuracy of double-ended impedance method is higher than single-ended impedance method.