Detection of Phony Data In PMU Measurements and Power Quality Assurance In Power Grids

In today's modern era advanced measurement devices such as Phasor Measurement Units (PMUs) and Phasor Data Concentrators (PDCs) are highly susceptible to Cyber-attacks, including denial-of-service (DoS) assaults and false data injection attacks (FDIAs), which accost newly imminent threats such as the power systems network stability, reliability, vulnerability, resilience, and security. In this research study, a potent low-rank tensor completion (PLRTC) technique is presented to handle issues like unobservability in PMUs measurement, cyber-attacks, and state estimation in power systems networks. Initially, a regularized low-rank tensor completion (LRTC) technique is presented to effectively exploit the inter-dependencies in the data for a robust recovery. Furthermore, for the low-frequency oscillation (LFO) identification, the bootstrap technique is implemented. Thereafter the free decay signals are separated from the single-mode signals for the identification of mode parameters by utilizing the random decrement technique (RDT) and Hilbert transform (HT). The efficacy & resilience of the potent LRTC technique is confirmed and contrasted with other recently discovered methods. Additionally, local area, two-area data, and real probing data from the Western Electricity Coordinating Council (WECC) are used to validate the proposed technique.