학술논문

Data Mining-based Techniques in Critical Operation of Electrical Transmission and Distribution Systems in a Natural Disaster Event: Future Direction Review
Document Type
Conference
Source
2019 IEEE International Systems Conference (SysCon) Systems Conference (SysCon), 2019 IEEE International. :1-8 Apr, 2019
Subject
Aerospace
Computing and Processing
Engineering Profession
General Topics for Engineers
Robotics and Control Systems
Hurricanes
Meteorology
Reliability
Data mining
Power system reliability
Circuit faults
Ocean temperature
Natural disaster management
Electrical System Resilience
Data Mining
Language
ISSN
2472-9647
Abstract
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.