Islanding Detection In Bulk Power Systems: A Data-Driven Approach

An attempt is made to propose a data-driven approach for detecting islanding in large-scale power systems. The method utilizes data collected by phasor measurement units (PMUs) to develop an equivalent model of the system. In this model, the system is represented by multiple centers of inertia (COIs) linked to a central point known as the center of gravity (COG) through fictitious reactances. These reactances, which are interpreted as the electrical distances between the local COIs and the COG, serve as a valuable indicator for detecting islanding. The occurrence of islanding can be identified by comparing the temporal trends of electrical distance variations across different areas. The effectiveness of the proposed methodologies is evaluated using simulated data from the 73-bus IEEE test system.