Analysis of power quality and temporary status using theory of wavelet

Electricity is one of the essential needs of modern society. It is easy to obtain. The increase in the number and the usage of electronic devices increase the need for electricity. The requirement of high-quality electricity is possible with adequately maintained electricity networks. The electric network generates electricity for a grid that is created to transmit electrical energy to users who need it. Electric network mainly consists of generator, transmission and distribution lines, in-between transformers and loads. The electricity, which is extracted at high voltages at the production points, is then lowered and distributed at lower voltages at the distribution points. Production and distribution organizations need to deliver high quality, cheap and uninterrupted energy to their users. Power quality is an essential factor in extending the life of electronic devices and preventing failures. Disruption of expensive electronic devices due to power quality causes problems between consumers and distributing organizations. This thesis aims to determine the deterioration of the quality of the power. Detection of deterioration provides the opportunity to take precautions. For this purpose, the system to be created uses Wavelet Transformation for feature extraction. Nine classes of power quality deterioration have been identified. Principal component analysis was used to reduce the number of features and accelerate classification. The performances of 21 classification methods were examined, and the most appropriate classification method was chosen. The results in the tables were obtained using the MATLAB program.