Fault Detection in Transmission Lines: a Denial Constraint Approach

Nicolas Tamalu, Leandro Augusto Ensina, Eduardo Cunha de Almeida, Eduardo Henrique Monteiro Pena, Luiz Eduardo Soares de Oliveira

Abstract: Resumo This paper introduces an approach for discovering denial constraints (DCs) to identify faults in transmission lines. However, the considerable volume of data in the studied scenario makes traditional DC discovery impractical due to lengthy execution times. We propose an alternative DC discovery approach that uses streaming windows to address this issue. Our experiments demonstrate that the DCs identified in pre-fault windows differ significantly from those in post-fault windows. This valuable insight enables us to detect faults autonomously, eliminating the need for human intervention (i.e., an unsupervised method). The experimental evaluation featuring diverse fault events reveals that our approach achieves fault detection with remarkable 100% accuracy.