1. A method of energy management in a power system comprising the steps of: Training an off-line neural network with load data; Training the off-line neural network with a first set of on-line predicted load values; Using the first set of on-line predicted values to predict a second set of predicted load values; Training an on-line neural network with load data; Training the on-line neural network with a third set of on-line predicted load values Using the third set of on-line predicted load values to predict a fourth set of on-line predicted load values Comparing the second set of predicted load values with actual load values and incrementing a first counter if the difference between the second set of predicted load values and the actual load values are within an acceptable range; Comparing the fourth set of predicted load values with actual load values and incrementing a second counter if the difference between the fourth set of predicted load values and the actual load values are within an acceptable range; and Calculating final predicted load values based on the values of the first and second counter.