A method based on independent component analysis for single and multiple power quality disturbance classification

• It classifies seventeen event classes with a performance above 97% for each class.
• It uses the ICA algorithm only in the design stage requiring no clustering stage.
• It is able to decouple the information between independent disturbance sources.
• In operation it requires simple filtering stage to decouple multiple disturbances.

This paper proposes a method based on single channel independent component analysis for single and multiple power quality disturbance classification. The proposed method decouples the power system signal into its independent components, which are classified by specialized classifiers. The classifier outputs are combined by using a logic that gives the final classification. Five classes of single disturbances and twelve of multiple disturbances are considered and a classification efficiency above 97% is achieved for each event class. Both qualitative and quantitative analysis elucidate the efficiency of the proposed method. Results are obtained from both simulated and experimental signals.