Spatio-temporal statistical identification methodology applied to wide-area monitoring schemes in power systems

Detection and characterization of the dynamic phenomena that arise when the power system is subjected to a perturbation become a significant problem. Therefore, a great deal of attention has been paid to identify oscillatory activity in interconnected power systems through the use of wide-area monitoring schemes. This paper presents a method for detection of propagation features from wide-area system measurements through its traveling and standing components, exploring the relationship between complex modes and the wave motion. The method consists in a biorthogonal decomposition considered from a statistical perspective which has the potential to be applied for wide-area monitoring and analysis using real-time synchronized measurements recorded from power systems. Although the technique is general, data obtained from global positioning system (GPS)-based multiple phasor measurement units (PMUs) from a real event in power systems are used to examine the potential usefulness of the proposed methodology. Furthermore, the decomposition technique based on optimal persistent patterns (OPPs) for time-varying fields is used to validate the applicability of the method.