Classification of Power Quality Events Using Wavelet Analysis and Probabilistic Neural Network

Abstrak

Power quality studies have become an important issue due to widespread use of sensitive electronic equipment in power system. The sources of power quality degradation must be investigated in order to improve the power quality. Switching transients in power systems is a concern in studies of equipment insulation coordination. In this paper a wavelet based neural network has been implemented to classify the transients due to capacitor switching, motor switching, faults, converter and transformer switching. The detail reactive powers for these five transients are determined and a model which uses the detail reactive power as the input to the Probabilistic neural network (PNN) is set up to classify the above mentioned transients. The simulation has been executed for an 11kv distribution system. With the help of neural network classifier, the transient signals are effectively classified.