Load forecasting for electric power distribution systems - De Castro, Arnulfo D. (1983)
The success of distribution expansion planning depends to a great extent on the accuracy of small-area forecasts. However, available extrapolation techniques such as curve fitting and curve shape clustering sometimes do not provide sufficient accuracy while simulation methods based on land use entail considerable expenses and large computer memory requirements. In this thesis, a method of improving the accuracy of trend forecasts, previously employed with curve fitting, is extended to forecasts developed through clustering. This method, called vacant area inference (VAI), involves adjustment of the initial forecasts in accordance with the more reliable system-wide forecast using estimates of horizon year load levels. The method was tested using a rectangular portion of Metropolitan Manila. The program was implemented on a microcomputer, making it a very attractive option for small utilities as well. The results of the study show the effectiveness of the approach, not only in adjusting forecasts of small areas with load history, but also for predicting loads of previously vacant areas.