Comparison between three back-propagation algorithms for power quality monitoring

In this paper Levenberg-Marquardt, Conjugate gradient, Resilient back-propagation algorithms are compared for power quality monitoring. Three Networks are trained in MATLAB. Each network is trained with the single algorithm mentioned above. Data for training is generated with the help of numerical model of power quality events in MATLAB. Voltage sag and swell is taken into consideration. The networks are so trained that it should detect and classify the voltage sag/swell accurately. Training performance of each network is presented with the help of performance and validation graph. Trained networks are tested with the help of simulation model. Simulation model is made in MATLAB which can generate sag/swell of any magnitude for any time period. Algorithms are compared on the basis of the ability of trained network to detect as well as classify the sag/swell and the performance of training.