Situational Awareness in Indian Power Grid using Synchrophasor Data

TL;DR

This paper demonstrates how synchrophasor technology and a combined Prony-FFT algorithm can enhance real-time situational awareness in the Indian power grid by detecting low-frequency oscillations during disturbances.

Contribution

It introduces a novel oscillation detection algorithm using Prony and FFT methods and validates its effectiveness on the Western Indian power grid.

Findings

The algorithm effectively detects low-frequency oscillations during grid disturbances.

Case studies show improved situational awareness with the proposed method.

The approach enhances grid stability monitoring in Indian power systems.

Abstract

Wide Area Measurement Systems (WAMS) can guide system operators' to increase their situational awareness by expanding observability of their supervise area and adjoining systems. Power system oscillations in the electrical grid are a matter of contention. It may transform the stable operation of the power system into an unstable system when oscillations grow and if no corrective actions are taken to mitigate them. This paper manifests the utilization of the synchrophasor technology for situational awareness by oscillation detection. An algorithm is proposed for the low-frequency oscillation-related analysis based on Prony and Fast Fourier Transform (FFT) methods. It gives better insight during the grid disturbance and other events related to power system operation. The effectiveness of this algorithm is validated by two case studies in the Western Regional Indian power grid.