Fault Detection and Localization Methodology for Self-healing in Smart Power Grids Incorporating Phasor Measurement Units

Abstract

Recent developments in several fields of engineering have accelerated the evolution of smart power grids encompassing both transmission and distribution systems across the globe. Self-healing, a crucial operational function of a smart power grid, requires detection as well as localization of the transmission line faults in the power network in real time. A support vector machine based fault-localization methodology has been proposed to accurately detect and localize any type of transmission line faults for the entire smart power grid. This methodology identifies the transmission line fault in smart power grid and precisely pinpoints the bus to which the faulty branch is connected. Afterward, the faulty branch is discriminated, and the distance of fault location from the bus related to the fault is estimated. The methodology relies on frequency-domain analysis of the equivalent voltage phasor angle and equivalent current phasor angle using fast Fourier transform. The proposed methodology has been corroborated using extensive case studies conducted on 7- and 13-bus power systems. The major contribution of the proposed methodology is that it can identify and localize all types of transmission line faults using phasor measurement unit measurements. The methodology can be applied for transmission systems as well as distribution systems.