Data-driven fault location approach in AC/DC microgrids based on fault voltage and current differences

Abstract

In recent years, various fault location techniques for microgrids have been presented. Some of these methods estimate the distance or section of the fault by assuming the availability of data from all measuring nodes, which is not economically viable. Moreover, the accuracy of these techniques is sensitive to the type of sources, fault location, resistance, inception angle, and they require accurate line models and enormous data banks. The prominent disadvantage of these methods is their performance for DC or AC networks separately. This article suggests a method to estimate both the distance of the fault and faulty section in a hybrid microgrid (DC/AC) using the π line model. This method begins by analyzing the voltages and currents of all buses based on the data collected at the points of common coupling and DG locations. Then, by analyzing the voltage and current difference at the buses of each branch, the fault location is determined. The proposed approach does not require DG models and needs a quarter of the data cycle. A 15-node hybrid microgrid is implemented in MATLAB, and a 7-node AC microgrid is implemented in the power systems simulator to evaluate the suggested technique. The results confirm the insensitivity of this approach to the different fault types, locations, inception angles, inductances, high impedance fault (500 Ω), DG operating conditions, and line parameters. In addition, the proposed algorithm is investigated by considering the measurement error. The results show the suitable accuracy of this scheme compared to other similar methods.