Fault location of active distribution network based on traveling wave feature classification
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Abstract:
With the access of distributed generator (DG), the power flow direction and structure of distribution networks have changed. Therefore, many traditional fault location methods are no longer applicable. Single-phase-to-ground fault is a common fault in distribution networks, which may bring secondary fault and even blackout. Based on the relationship between the wavelet eigenvalues of traveling waves and the fault section of distribution lines with DG, the optimal fault features were selected by dimension reduction of linear discriminant analysis (LDA), and then the Bayesian construction classification model based on kernel distribution was used to realize a new method of single-phase-to-ground fault location. The IEEE 33 bus model with DG was constructed to test the faults in different sections of active distribution networks. The location accuracy of the optimal three-dimensional feature sample reached 97.9%, demonstrating that the proposed method can achieve accurate fault location.
