High Impedance Faults Detection and Classification in Renewable Energy-Based Distribution Networks Using Time-Varying Kalman Filtering Technique

Abstract

In the modern world, High Impedance (HI) Faults’ identification is challenging in renewable energy-based distribution networks (REBDNs) due to the low level of the fault current. In this paper, a new HI fault detection/classification strategy is presented for REBDNs, based on the time-varying Kalman Filter (TVKF). Initially, TVKF is applied to the voltage and current signal of each phase separately, in order to extract harmonic components. Secondly, the TVKF-based harmonic components are utilized to calculate the single-phase reactive power (SPRP) independently. If the SPRP of any individual phase is greater than a specific threshold value, the corresponding phase is considered faulty. Fault classification is autonomous due to phase segregation. The proposed strategy is tested on the REBDNs’ test system in MATLAB/Simulink software. The results indicate that the proposed scheme detects and classifies HI faults under radial and mesh topologies.