A REAL-TIME IMPLEMENTATION OF SHORT-TERM LOAD FORECASTING FOR DISTRIBUTION POWER-SYSTEMS

This paper presents a practical real-time implementation of weather adaptive short-term load forecasting for distribution power utilities. The implementation is accomplished by utilizing a comprehensive load forecasting model consisting of time series, nonlinear load-weather functions and a residual load function represented by an ARMA (Auto-Regressive Moving Average) model. The model parameters are estimated and updated on-line using the WRLS (Weighted Recursive Least Squares) algorithm. A variable forgetting factor (VFF) technique is incorporated in the WRLS algorithm for improved model tracking and numerical performance in real-time operation. A software package, STLF, is developed with the proposed implementation method or distribution power utilities. Practical operation of the STLF in several power utilities has demonstrated great successes. Off-line testing and on-line operation has consistently shown satisfactory performance with the mean absolute error(MAE) mostly less than 2 % for a less than 24-hour ahead forecast and less than 2.5 % for a less than 168-hour ahead forecast.