Autonomous Detection of Nearby Loss of Generation Events for Decentralized Controls

Abstract

A broad scope of this dissertation is to verify that a nearby loss of generation event in power system can be distinguished from similar remote disturbances by analyzing the resulting local modes of oscillation. An oscillation-based index derived from methods like Fourier transform, sinc filters and resonant filters is devised and experimented in combination with a variant of df/dt index to jointly classify if a loss of generation event is nearby or remote. A phenomenon widely observed during a loss of generation event is the average decrease in the system’s frequency, typically monitored using the df/dt index. Under-frequency load-shedding (UFLS) relays that are based on df/dt are highly likely to trip for nearby frequency events when combined with the oscillation-based index we propose. Nearby in our context refers to geographical distance, which is correlated with electrical distance, and includes buses within about 50-100 miles of the event location.