One-Ended Fault Location Method Based on Machine Learning Models

One-ended impedance based algorithms are the most widely used in fault location, but are prone to several sources of error. In order to overcome these limitations, this paper proposes a new method based on machine learning techniques that uses only the current signals from one of the terminals of the protected line. Clarke's transformation and discrete wavelet energy distribution are used to process the signals, yielding satisfactory results.