Power quality disturbances recognition based on Hyperbolic S-transform and rule-based decision tree

Power quality disturbances recognition is the foundation of power quality analysis and control. A novel high performance recognition method based on a generalized S-transform with Hyperbolic window (Hyperbolic S-transform) and rule-based decision tree is proposed in this paper. The original power signals are analyzed by the HS-transform. 4 features are extracted to formulate decision rules. Finally, a rule-based decision tree is constructed to classify power quality disturbances. 8 types of power quality disturbances including 2 types of complex power disturbance are recognized precisely by the decision tree. The new approach has simple classification process and high classification effectiveness. It is very satisfied for the real-time requirement of smart grid in real work. The simulation result shows the robustness and effectiveness of proposed method.