IEEE Electrification Magazine · 2021 · 12 citations · 0 references
ComputingComputer ScienceElectrical EngineeringCritical Infrastructure ProtectionMachine LearningStatistical LearningEnergy Infrastructure ProtectionFault DetectionPower SystemsProtection SystemsFault Detection Using Machine LearningMachine Learning For Fault DetectionMachine Learning For Smart GridsMachine Learning-based Fault DiagnosisPower System Protection
This article presents our view of why machine learning (ML) has not been able to find its way to commercial products in the field of protection. All the methods we have reviewed in the literature essentially propose some ML-based technique to replace a legacy protection scheme. The results are substantiated by training and testing ML models through simulated data. Legacy methods, on the other hand, are developed using mathematical models that capture the physics of disturbances and faults.