Model identification in peak power demand forecasting

Peak Demand model for an electric utility is formulated in terms of demographic, economic and climatological variables. Since significant correlations generally exist among these variables, conventional regression analysis cannot be used for model identification due to the problem of multicollinearity. An improved approach, using principal components, is described which eliminates the problem. The approach was successfully used at Southern California Edison Company for developing long-term peak demand forecasting models.