Harmonic distortion assessment and visualization for power transmission systems

Abstract

There are multiple situations in which the amount of harmonic content data represents a challenge to obtain pertinent diagnosis on the long-term operation of the grid. However, descriptive statistics can be applied to big data sets of power quality measurements to enhance the situation awareness of complex power systems. This paper presents a methodology that allows operators to synthesize large amounts of power quality data. The approach is intended to be applied based on information collected by a fault recorder module at the electrical substation. With big data analysis techniques, the proposed methodology allows users to extract information and analyze two proposed indicators to alert the utility operator about critical conditions of harmonic content. The methodology is applied to a case study where millions of real power quality records were analyzed to show evidence about certain transmission system performance.