Large power network signature analysis with PMU signal-dynamic clustering approach

The paper presents signature analysis of large power network with Phasor Measurement Unit (PMU) signal using dynamic clustering approach. This concept may become more useful for system operators having large numbers of PMUs deployment in utility power network for observing the variations due to dynamical changes. It is well known as more numbers of PMUs are introduced in the network, there is an exponential increase in data which may require a special technique to understand the behaviour of entire system within time for generating quick control actions for system regulation. In present work, the concept of Clustering Algorithms (CA) to mine the synchrophasor data from PMUs has been applied with practical utility data (POWERGRID). Due to large data generated by PMUs, it becomes imperative to mine data so that important information from dataset can be utilized for monitoring of grid health followed by modified control in order to realize effective system operation. The procedure for extracting information from this data has been discussed through clustering algorithms.