Power Quality Disturbance Recognition Based on Fitting Redundant Lifting Wavelet Packet and Energy Analysis
Zijing Yang, Guang Xu Ren · 2017
To realize accurate detection and recognition of power quality disturbance, a fitting redundant lifting wavelet packet method combined with energy analysis is proposed in this paper. As six new wavelets obtained through data fitting and lifting algorithm are employed for disturbance analysis, two issues i.e. selection of both the wavelet and the node signal are well investigated, while the energy analysis is utilized to distinguish the type of power quality disturbance. Simulation results show that distinct selection of wavelet or node signal will leave different impact on disturbance detection, and with energy analysis two types of power quality disturbance i.e. the voltage swell and voltage sag can be easily and precisely recognized.