Voltage Sag State Estimation using Compressive Sensing in Power Systems

This paper presents a new formulation of the voltage sag state estimation problem based on compressive sensing theory. The growing economic losses for voltage sags have led to a search for new mathematical methods for voltage sags diagnosis. Several studies have been focused on optimization problems based on techniques that are inaccurate when faults with large impedance are considered. To overcome these limitations, we proposed a $\ell 1$-based voltage sag state estimator ($\ell 1$-VSSE). A limited number of voltage sag meters, sensing matrices using residual voltages per unit, and the solution of a $\ell 1-$ regularized least square problem (LSP) for each voltage sag detected, are novel characteristics of the proposed estimator. The $\ell 1$-VSSE has been validated by using the IEEE30-bus power system and the IEEE69-bus distribution system. The outcomes validate the efficient performance in the voltage sags estimation and its robustness to the fault types, fault impedance, and meshed or radial systems.