Synergism of synchrophasor measurements and data analytics for enhancing situational awareness of power grid

Abstract

This study aims to demonstrate the real-world experience of integrating multi-location high-granularity synchrophasor measurements and various data analysis techniques to perform disturbance analysis and enhance the situational awareness of a power grid. It describes the utilisation of box plots, correlation techniques, and clustering techniques. These are applied to synchrophasor measurements obtained from 400 kV substations of the Maharashtra State Electricity Transmission Company Limited in the western part of the Indian grid to elucidate the behaviour of the grid under ambient and disturbance/event conditions. The results illustrate how correlation technique can serve as important decision-making tool for system operators in managing the grid. The application of various clustering techniques (such as k-means clustering, hierarchical clustering, and partitioning around medoids) to synchrophasor data to determine the number of clusters formed is also discussed. Internal validation techniques are applied to verify the effectiveness of the clustering algorithms.