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 online 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 for distribution power utilities. Practical operation of the STLF in several power utilities has demonstrated great success. Offline testing and online 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.<
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