Chapter 5 - Wide-area monitoring and estimation systems

Abstract

Modern power grid is a generation mix of conventional generation facilities and variable renewable energy resources (VRES). The complexity of such a power grid has urged the utilization of infrastructures involving phasor measurement units (PMUs) to have access to real-time grid information. However, the traffic of digital information and communication is prone to data-injection and cyber-attacks. To address this issue, a median regression function (MRF)-based state estimation is proposed. The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. An exogenous function-based representation of the state is considered for the system. A mapping function-based initial regression analysis is made to depict the margins of state estimate in the presence of data-injection. A median regression function is built on top of it while generating and evaluating the residuals. The tests were conducted on a revised New England 39-Bus system with large scale PV power plant in the presence of harsh data-injection attacks and multiple system disturbances. Results show the proposed MRF method can accurately estimate the states and evaluate the contaminated measurements.