A Data-Driven Transient Stability-Based Approach for Out-of-Step
Prediction in Power Systems
Abstract
This paper presents a decentralized prediction-based algorithm designed
to address out-of-step (OOS) conditions in power systems. The algorithm
utilizes generator data obtained from phasor measurement units. The
transient stability of a multi-machine power system is evaluated using
the equal-area criterion (EAC). The proposed algorithm calculates the
characteristics of the P-δ curves within the EAC framework after a large
disturbance. The critical P-δ trace is determined by analyzing the
cumulative energy in the acceleration area following fault clearance.
The stability margin of the rotor angle is then computed based on the
actual active power and its relationship with the critical curve. The
algorithm predicts the occurrence of OOS by comparing the measured
active power with the corresponding value on the critical curve. The
effectiveness of the proposed algorithm is validated through simulations
conducted on the 73-bus IEEE test power system.