Classification and identification of SAG waveform using MATLAB application in power quality analysis / Mohd Syamsul Bahri Hassan

Voltage sags are common events on the electric power network. They are caused by network faults and the connection of large loads. They can affect a wide range of electrical equipment and are of particular concern to industry. Sags can be characterized by their depth and duration but careful consideration need to be given to sag occurring simultaneously on several phases or occurring in quick succession. Individual sites can be assessed for their sag performance using sag indices which use statistical methods to give a number which represents sag performance and which can be used to compare to other sites. This paper presents an approach that is able to provide the detection and location in time as well as the classification and identification of power quality problems present in both transient and steady-stable signals. The method was developed using MATLAB 5.3 software by THE MATHWORKS INC and executed under windows operating system. The given signal is decomposed through wavelet transform and any change on the smoothness of the signal is detected at the finer wavelet transform resolution levels. Later, the energy curve of the given signal is evaluated and a relationship between this energy curve and the one of the corresponding fundamental component is established using probabilistic neural network (PNN). The paper shows that each power quality disturbance has unique deviations from the pure sinusoidal waveform and this is adopted to provide a reliable classification of the type of disturbance.