A Novel Hybrid Algorithm for Event Detection, Localisation and Classification

Effective management of multiple real-time transient events and unstable low-frequency oscillations in the modern power system has been a matter of concern to the Transmission system operators. This manuscript unifies the idea of transient event detection and localization with the analysis of the oscillation mode that accompanies these impulsive events. The paper employs Discrete wavelet transform (DWT) to segregate transient events from oscillatory behavior that follows these events. The paper also proposes a novel indicator for the classification of transient events based on the most affected signals in due course of the event. Empirical Mode decomposition (EMD) and Hilbert spectral analysis (HSA) are utilized on the PMU signals severely affected by the event and further examine the oscillatory modes succeeding the real-time events. Oscillatory modes deduced from the above adaptive transformations are further categorized into three frequency bands based on power system control applications, thus helping operators provide efficient control actions. The novel methodology discussed in the paper has been applied to the IEEE 39 bus system with a dataset generated using the RTDS power system simulator and GTNETx2 based PMUs.