High impedance fault detection method efficiency: Simulation vs. real-world data acquisition

In this paper, the reliability of a novel high impedance fault (HIF) detection method is compared for two data acquisition cases, namely, real-world and simulation. The real-world data is collected in high current research laboratory, and the simulation data is acquired using PSCAD/EMTDC software. The real-world condition is set to the most practical conditions (noisy environment, magnetic-core CTs). It is observed that although the proposed HIF detection method shows perfect reliability for the simulated HIF, its reliability for real-world data is considerably lower. From the comparison between the proposed detection algorithm reliability between the simulation and real-world data, it is concluded that it is not sufficient to prove the method reliability solely using the data acquired from simulation or impractical real-world cases, measurement noise. In order to increase the method reliability for real-world data, four actions are proposed in this paper; using a more complex classifier, a larger feature set, a wavelet based de-noising algorithm, and decreasing the method speed.