Short Duration Voltage Disturbance Identification using FFT Algorithm in Distribution System

Power quality issues have been a source of major concern in recent years due to extensive use of power electronic devices and non-linear loads in electrical power system. In power systems the common disturbances are voltage sags and swells, usually associated with power system faults. Therefore the effective detection of voltage sags and swells event is an important issue for both voltage sag and swell analysis and mitigation. There are several detection methods for voltage sags and swells such as RMS voltage detection, peak voltage detection, and Fourier transform methods. The most common method used for this is Fast Fourier transformation (FFT) Algorithm, the purpose for using this method is calculation of the root mean square value of the voltage supply. Using the same method that is the calculus of the RMS voltage on a cycle updated every half of cycle. The main objective is to be proposing a Fast Fourier transformation (FFT) algorithm for rapid voltage sag, swell and sag-swell detection better than other methods. This algorithm has the ability to track the amplitude of the voltage sag and swell in real time. Proposed RMS algorithm was compared to existing sag detection methods to show its fastness and robustness. The algorithms for voltage sag and swell detection using MATLAB/SIMULINK software.