Diagnóstico de fallas en líneas de transmisión de energía eléctrica empleando métodos de inteligencia artificial

Abstract

The reliability and continuity of electricity supply are essential for economic and social development, which is why electrical grids must operate under high standards of safety and efficiency. These grids play a fundamental role in connecting generation systems with end users through energy transmission, distribution, and transformation infrastructure. Due to their strategic importance, any disruption in their operation can have significant impacts on both productive sectors and the population's quality of life. In this context, fault analysis in transmission lines becomes crucial, as it allows for the timely identification of the causes of events that affect system stability. The detection and proper classification of faults facilitates the implementation of rapid corrective actions, helping to reduce service interruption times and the costs associated with restoring normal operation. Likewise, protection systems play an essential role by isolating affected components and preventing disturbances from propagating to other parts of the grid. The vulnerability of transmission lines to atmospheric phenomena and diverse geographical conditions increases the need to develop advanced monitoring and diagnostic methods. Therefore, strengthening protection and failure analysis strategies is essential to ensuring safer, more resilient, and more reliable electrical systems