A Data Driven Detection and Locating of Cyber and Physical Stresses in Smart Grid based on State Correlations

Smart grids being complex cyber-physical infrastructures demand real-time monitoring of their dynamic states. Phasor measurement units (PMUs) are smart metering devices with a high sampling rate, which facilitate visualizing the dynamics of the states with the help of time series corresponding to the system's parameters and attributes. This work shows the signatures of different cyber-attacks and some physical phenomenons on the PMU time series and their impacts on the correlation among the components' states. A technique exploiting the instantaneous state correlation matrix (associated with any electrical attribute, i.e. bus voltage angle) is proposed for providing early alerts for attacks to the control center's operators in real-time. The type of attack (cyber or physical) and the location of the component that is compromised by the attackers are also detectable by observing the instantaneous correlation matrix as an image.