High Impedance Fault Detection Algorithm using Frequency-Based Principal Component Analysis
Keywords:Fault Detection, High Impedance Fault, Principal Component Analysis
An exposed energized conductor may cause fire, a huge release of energy and a high risk to human life and the undetectable fault is a serious issue to the public safety hazard and risk of arcing ignition of fires especially when it comes in contact with trees, structure or fall to the ground. However, it is undetectable by the conventional overcurrent protection system as the current maintained at low level. This particular project focuses on modelling high impedance fault (HIF) using Emanuel arc model constructed in MATLAB Simulink and applied it to the IEEE 13 node test feeder circuit model. Principal Component Analysis (PCA) algorithm is developed and implemented to the system in order to detect the HIF in the system based on the change in frequency of the current. It is proven that the presence of HIF in the system caused high frequency in current value. Hence, it is concluded that the presence of HIF in the system results in the PC3 value to be low (-0.1 ≤ PC3 ≤ 0.1) and spike in frequency to be more than 60Hz. The characteristics of HIF for power system is analyzed and the HIF has been successfully modelled based on its characteristics in time-domain simulation. The occurrence of HIF in power system is successfully detected using the time-series analysis method.