ANN-TW Analysis Based Transmission Line Fault Identification and Location with High Penetration of Inverter-Based Resources

A Power systems are undergoing a rapid change in generation mix due to the growth of Inverter-Based Resources (IBRs) such as wind and solar PV. This rapid growth creates new challenges for protection engineers. The output current of an IBR facility under short circuit conditions differs significantly from that of a conventional rotating synchronous source facility, posing protection problems. The protection schemes for the transmission line, which were designed locally at the planning stage, may operate reliably for low penetration of IBRs but in the case of high penetration, fault detection and location in the transmission line will be challenged. In this paper, a traveling wave-based protection schemes with the aid of Artificial Neural Network (ANN) as an innovative method to overcome these challenges and facilitate the widespread deployment of IBRs in transmission systems will be presented. A three-bus transmission network with voltage level of 380Kv and 94% of renewables penetration is simulated using DIgSILENT Power Factory is used in this study. The results demonstrates that fault identification is a quick and reliable way to identify a variety of faults, particularly single line to ground faults, which are the most challenging fault for the protection system.