A New Scheme for Swing Detection and Stability Assessment in Power Systems using Private Wide Area Networks and Public IoT

This paper presents a new scheme for power swing detection and stability assessment for multi-machine power systems that adopts Smart Grid perception. It is an asynchronous scheme that uses the rate of change of the generator angle for stability assessment rather than estimating the value of the absolute angle using synchronized measurements, therefore, no Phasor Measurement Units (PMUs) are required. It presents a novel use of the multicast GOOSE protocol or its routable counterpart (R-GOOSE) to convey the disturbance in the power grid to the data transmission pattern over private Wide Area Networks (WANs), which is the most controlled state. The scheme is extended further to the public Internet of Things (IoT) as it has been proven to deliver high performance service when applying 5G technologies. The new scheme is validated by introducing disturbances on the simulated IEEE 39 Bus System and testing the transmitted GOOSE packets over private network. Next, the IoT 5G network is studied for GOOSE transmission using a time efficient tunneling mechanism. The results reveal that the scheme is capable of differentiating between stable unstable swings. Furthermore, it predicts the instability before its occurrence by more than 100 ms for both private WAN and IoT, which either meets or outperforms the existing PMU-based techniques.