Identification and Analysis of Electrical Storms Features Using Clustering Numerical Methods

Abstract

Lightning strokes are natural phenomena responsible for a large number of disturbances and interruptions in electrical systems. The investigation of their behavior can support operation strategies and installation and protection projects of power transmission lines. This research scope includes the study of joint development of lightning strokes, in space and time, as result of structured weather events called “electrical storms”, and the analysis of their behavior near a selected electrical system. To identify and track these storms a clustering method of Convergent Data Sharpening is used, and to analyze the trajectories behavior formed by these storms regarding meteorological features the  Self-Organizing Map (SOM) is applied. Both methods are implemented in software package R. The study revealed that electrical storms that caused failures in the electrical system studied tended to have more lightning strokes than other storms and also had no peak current average greater than regular storms, what could be expected by the relevance of this variable in the electrical system disturbances.