The investigation of power quality in power systems by using discrete wavelet transform

In this thesis, the description of power quality which has a great importance due to the technological developments is introduced; the factors affecting the power quality and the types of power quality disturbances occurred as a result of these factors in power systems are investigated. The data set which is needed for the analysis of principal power quality disturbances occurred in power systems is obtained by using the mathematical equations in Matlab software. Power quality disturbance signals obtained from the mathematical equations are analyzed by using the signal decomposition feature of discrete wavelet transform due to the fact that power quality disturbance signals are not stationary structure and these signals contain disturbances, different frequency components and energy distributions. From the results of analysis, important informations including starting and finishing times of disturbances and the elapsed time during the disturbances occurred are obtained. Then, two different feature curves are obtained by using the energy and norm entropy feature extraction methods which reduce the data set in size without losing the distinctive features of power quality disturbance signals. The distinctive features of the disturbance signals are extracted by comparing these feature curves with a reference signals visually. By analyzing the feature curves, it is shown that norm entropy feature extraction method has a better ability of distinction and the disturbance signals can be classified easily even naked eye.Key Words: Power systems, Power quality disturbances, Wavelet transform Feature extraction.