Autonomous Detection of Nearby Loss of Generation Events for Decentralized Controls
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.
Autonomous detection, Location targeted under frequency load shedding (LT-UFLS), Decentralized controls, Nearby loss of generation events, Local modes of oscillations
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