Automatic contingency grouping using partial least squares and feed forward neural network technologies applied to the static security assessment problem

The paper shows how a number of feed forward back propagation neural networks can be trained to predict power system bus voltages after a contingency. The approach is designed to use very few learning examples. thus being suitable for on-line use. The method was applied to the 10-machine, 39-bus New England Power System model.