Power Quality Feature Modelling of Waveform Disturbances for Distribution System Diagnosis

This paper presents a Power Quality (PQ) modelling and filtering processes for the distribution system disturbance recognition learning. typical PQ waveforms with mathematical applications and gathered field data are applied to our models. The process has modules to obtain the waveforms of incipient failures or abnormal operations, trouble condition waveforms in the distribution system through feature extraction and trigger condition techniques. In this regard, we found that proposed extraction criteria of determination rules can interact suitably with our parameter update method to detect and containing the waveforms. Therefore, the recurring analysis can classify the event conditions and ensures disturbance and fault recognitions which containing the waveform information.