Classification of Power Quality Disturbances Using Wavelet Transform and Halfing Algorithm

ABSTRACT There is demand for power supply with higher quality by consumer around the world. Disturbances caused by inductive loading, local and remote faults, capacitor switching, poor power factor, lack of Var support, system voltage regulation, transformers and generators, AC motor drives can affect electricity usage causing tripping of sensitive equipment, resetting of control system, damage of power supplies for electronics equipment without backup supply facilities, problems with equipment that requires constant steady-state voltage, mal-operation of sensitive equipment and relays and flicker in incandescent lamps. Thus there is need to identify different kinds of disturbances and take steps to mitigate them. This paper present a power quality disturbance classification technique based on wavelet transform and halfing algorithm. Wavelet transform is used to find the interval of the disturbance and thus isolate the disturbance signal. The isolated signal is then transformed into a 2-dimensional image, characteristic map, with halfing algorithm. The thus generated characteristic map clearly classifies and identifies the type of disturbance and can be processed further with classification methods such as clustering for automation purposes. Keywords: Wavelet Transform, Halfing Algorithm, Power Quality, Power Disturbances