1. A method of energy management and short term load prediction in a power system, comprising the steps of: dividing a time period into a plurality of sub-periods; using a plurality of neural networks, each of the plurality of neural networks comprising a plurality of neurons to predict a short term load demand on the power system, the sub-periods being further divided into predicting intervals and assigning one of the plurality of neural networks to each of the plurality of sub-periods; receiving historical load data and a short term load forecast (STLF) for a STLF interval which is greater than or equal to the largest prediction interval; and using the output of each of the plurality of neural networks to predict the short term load demand in each predicting interval.