A genetic based algorithm for measurement of power system disturbances

This paper introduces genetic algorithms (GA) as a powerful tool for monitoring and supervising power system disturbances generated due to dynamic performance of power systems. Monitoring power system disturbances involves monitoring fundamental voltage magnitude and its frequency as well as harmonic and sub-harmonic voltage magnitudes and their frequencies under different operating conditions for power quality evaluation purposes. The proposed method is based on genetic algorithms optimization technique. The method uses digital set of measurements for the voltage or current waveforms at power system bus to perform the estimation process digitally. The algorithm is tested using different simulated data to monitor power quality. Three different study cases are considered in this work. In the first part, the estimation of voltage flicker levels and its frequency is presented and discussed. In the second part, the frequency of a bus voltage signal that is contaminated with harmonics is estimated. The harmonic contents are also estimated in this case. In the third part, the analysis of a damped sub-harmonic signal is presented. Effects of number of samples, sampling frequency and the sample window size are studied. Effects of GA parameters and operators, such as population size, crossover, mutation probabilities and niching are also studied. Results are reported and discussed.