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This paper describes the third generation of an hourly short-term load forecasting system known as ANNSTLF (Artificial Neural Network Short-Term Load Forecaster). This forecaster has received wide acceptance by the electric utility industry and is being used by 35 utilities across the US and Canada. The third generation architecture is substantially changed from the previous generation. It includes only two ANN forecasters, one predicts the base load and the other forecasts the change in load. The final forecast is computed by adaptive combination of these two forecasts. The effect of humidity and wind speed are considered through a linear transformation of temperature. A novel weighted interpolation scheme is developed for forecasting of holiday loads, giving improved accuracy. The holiday peak load is first estimated and then the ANNSTLF forecast is re-shaped with the new peak forecast. The performance on …