An Approach for Discriminating Abnormalities In Compensated Power Transmission Circuit

In this paper, an intelligent fault diagnosis approach has been presented for compensated power transmission circuit (CPTC) system. The proposed approach is based on the application of signal processing and machine learning techniques. Discrete wavelet transform (DWT) has been applied on the 3-phase current transient signals for seizing the apt characteristics of the signal during different abnormality occurrences. The same signal features data has been utilized by ML model for the diagnosis of abnormalities in the CPTC system. Various test analysis (taking different possible abnormality in the system) has been performed in digital simulation for weighing the applicability and efficiency of proposed protection approach. The results of different cases have reaffirmed the application of proposed fault diagnosis approach for modern CPTC system.