Biological Interactions in Distribution Networks and Analysis of Weather-Related Failures Using Artificial Neural Networks

Overhead line faults have a critical impact on the reliability of electrical distribution systems. Literature reviews show that overhead lines are highly susceptible to environmental factors such as weather conditions, vegetation and wildlife. This study presents a data-driven approach to analysing biologically induced outages in overhead distribution lines using Artificial Neural Network (ANN) techniques. The study aims to predict regions where outages are likely to occur using meteorological data. For the analysis, real outage data from an electricity distribution company for the period 2021-2023, together with meteorological data for the same period, were used to model the ANN structure in MATLAB software. The model achieved an accuracy rate of 97% on the test data, demonstrating a high generalisation ability. The results of this study provide valuable insights for electricity distribution companies to better understand biologically induced outage problems, and to develop effective models for predicting such outages.