Combined Detection and Localization Model for High Impedance Fault under Noisy Condition

Detecting and locating High Impedance Faults (HiZ) is difficult due to the small magnitude of fault current during such faults. In this work, we propose a combined HiZ fault detection and localization technique that uses voltage and current measurements available from existing intelligent electronic devices (IEDs). At first, we apply the variation mode decomposition (VMD) model to detect the existence of fault based on denoised time series of measurements using Wavelet Transform (WT). After detecting the presence of fault, we apply the correlation based matrix to locate the suspicious fault locations, and then utilize K-nearest neighbour (KNN) to identify the faulty branch among those locations using dynamic time warping method to measure the distance between neighbors. Finally, we verify our proposed model with simulation results on an inverter-based microgrid. Outcomes from VMD method demonstrate that measurement from any location of the grid can indicate the existence of HiZ fault over the duration of the event, and show the scalability of the proposed method. For localization, it is verified that the correlation matrix combined with KNN can remove the false positive cases with properly tuned KNN-parameters and correlation matrix threshold, irrespective of the measurement noise.