Joint VAr controller implemented in an artificial neural network environment

Artificial neural network software has been trained to perform the joint VAr control function and demonstrated on three large synchronous condensers. Training rate depends on the nature of the training data set. It is noted that training data sets should be designed to place the majority of the data in the areas where the transfer function is the most critical