In this paper, comparison of seven backpropagation algorithms used in neural network is made for the three phase power quality assessment. Voltage sag and swell are the two disturbances taken into account for comparing the algorithms. These disturbances are generated with the help of programming in MATLAB. The input data, to train the network is the generated sag and swell disturbances. The backpropagation algorithms are taken into account for comparison are conjugate gradient descent, Levenberg-Marquardt, one step secant, Baysian regularization, scaled conjugate gradient descent, gradient descent with momentum and gradient descent with adaptive learning rate. The seven algorithms are used to train the seven networks and tested using simulation model in MATLAB. After testing is done, the comparison is made on the basis of mean squared error, number of neurons, percent of accurate cases detected, number of iterations required for the training process. The testing results for the each algorithm and comparison are presented.