Weather-normalized intermediate term capacity forecasting: a procedural innovation

The authors present the theoretical foundations of a procedural innovation for weather normalization of hourly loads. They describe an alternative statistical approach that will produce efficient estimators in the presence of complex serial correlation in the model´s error structure E.J. Hannan´s efficient estimator (1970), a form of frequency-domain regression analysis, was used to develop efficient hourly load/weather equations. From then-normalized load database, monthly peaks were extracted. Box-Jenkins (B-J) analysis was performed on these monthly peaks for production of 24-months intermediate forecasts. The results of these forecasts were compared with B-J forecasts prepared from actual monthly peaks. Of the 12 forecasts compared, the average monthly error for 11 was reduced by 50% or more. For 9 of these forecasts, the error reduction was 66% or more.<>