Development of cluster algorithm for grid health monitoring

Abstract

The paper describes the use of K-means clustering algorithm to mine the Synchrophasor data from PMUs. PMUs are newly developed tools for monitoring the grid health by measuring grid parameters such as voltage, current, frequency, rate of change of frequency and phase angle with high sample rate and time stamping. The large amount of data produced by PMUs can help the grid operator for stable operation of the grid. But such data cannot be useful until it is mined appropriately using different methods. Application of k-means clustering algorithm is useful for extracting important information from the Synchrophasor data. This information helps the operator to take real time decisions and ensures the grid stability. © 2016 IEEE.