High-speed and accurate detection of high-impedance arcing faults in renewable energy microgrids using a master-slave ADALINE algorithm

High-Impedance Arcing Faults (HIAFs) in electrical microgrids are among the abnormal conditions that are difficult to detect by conventional protective devices due to low current and non-linear behavior. In addition, the behavioral similarity of HIAFs to other transient events (TEs) in microgrids leads to classification challenges. This study addresses this issue by proposing a new protective algorithm for the fast and accurate detection of HIAFs and their differentiation from other TEs. The proposed method uses the third harmonic angle of the residual current (THARC) as a key identification feature, which is extracted using a fast, accurate two-layer Master-Slave ADALINE (MS-ADALINE) architecture. The THARC is then smoothed using the Moving Average (MWA) technique, and a new index is introduced for fault detection. Simulations conducted in the EMTP-RV software environment demonstrate that the proposed algorithm can distinguish HIAFs from other TEs under noisy and complex conditions with an accuracy of 99.17% and a detection time of 20 msec. Low computational cost and simple, practical implementation are additional significant advantages of the proposed method.