Data Mining-based Techniques in Critical Operation of Electrical Transmission and Distribution Systems in a Natural Disaster Event: Future Direction Review

摘要

Warming trends and increasing temperatures have been observed and reported by federal agencies, such as the National Oceanic and Atmospheric Administration (NOAA). Extreme weather, especially hurricanes and tornadoes, are among the highly devastating natural disasters responsible for massive and prolonged power outages in Electrical Transmission and Distribution Systems (ETDS). Our approach is motivated by the integration of two application domains: First, the critical operation of the ETDS systems under natural disaster conditions. Second, Data integration based on Data Mining techniques like Machine Learning, Deep Learning and Knowledge Discovery methodologies. This paper provides a brief review of both domains, as well as the knowledge gap and future research directions that will benefit the resilience of the ETDS systems under natural disaster conditions.