SHORT-TERM LOAD FORECASTING FOR DEMAND-SIDE MANAGEMENT

A method for short-term load forecasting which would help demand side management is presented. This is particularly suitable for developing countries where the total load is not large, especially at substation levels, and the data available are grossly inadequate. It is based on the Kalman filtering algorithm with the incorporation of a 'fading mem ory'. A two-stage forecast is carried out, where the mean is first pre dicted and a correction is then incorporated in real time using an err or feedback from the previous hours. This method has been used to pred ict the local load at 11kV and also the bulk load at 220kV. The result s and the prediction errors are presented.