An artificial neural network based digital differential protection scheme for synchronous generator stator winding protection

This paper describes a new artificial neural network (ANN) based digital differential protection scheme for generator stator winding protection. The scheme includes two feedforward neural networks (FNNs). One ANN is used for fault detection and the other is used for internal fault classification. This design uses current samples from the line-side and the neutral-end in addition to samples from the field current. Fundamental and/or second harmonic present in the field current during a fault help the ANN, used for fault detection, to differentiate between generator states (normal, external fault and internal fault states). Results showing the performance of the protection scheme are presented and indicate that it is fast and reliable