Fault Detection in Distribution Networks with Distributed Generation: A Practical Guide to the Morphological Median Filter for the Feature Extraction of Faults

In this paper, a signal processing method based on Mathematical Morphology (MM) is developed, designed to extract representative characteristics of signals that allow the identification and detection of various types of faults in distribution network feeders that incorporate distributed generation with inverter interfaces (IIDG). The goal is to improve the performance of the fault protection system, ensuring rapid, sensitive, and reliable detection. The fault detection method presented in this article employs a well-known signal processing filter, called the morphological median filter (MMF), applied to the current measured at the current transformer (CT) associated with the relay located at the head of a feeder in a medium-voltage distribution network with IIDG. The extracted characteristics will be used in future research to detect and classify events, such as short-circuit faults or operational manoeuvres, thus facilitating the implementation of protection strategies.