Configurable stochastic model for high impedance faults simulations in electrical distribution systems

Abstract

High Impedance Faults (HIFs) detection is an unsolved problem in electrical distribution networks, mainly due to its unpredictable behavior and low current levels. Many HIF detection methods have been proposed in the literature so far. The vast majority of them use simulated data to test and validate the method due to the difficulties in obtaining actual data. However, the HIF models proposed in the literature do not accurately reproduce the electric arc, especially its stochastic behavior. As a consequence, the methods based on simulated data may fail for real-life situations. To fill this gap, this paper proposes a new HIF model that does not depend on actual data and is capable of generating random signals that reproduce all HIF characteristics. The model architecture is another novelty: it is modular, so HIF characteristics can be reproduced isolated or simultaneously, including its stochastic behavior, making it a powerful tool to test and validate HIF detection algorithms. The model has been validated by using both literature and field data.