Abstract
The paper presents local dynamic approach to fusion of results of many predictors, forecasting the 24-hour load pattern in electric power system. The prediction of 24-elements vector for the next day power need is done here using one member of an ensemble, which was the best in the learning stage for the input vector, closest to the actually applied input data. This way we get the highest level of statistical forecasting accuracy, since each task is performed by the predictor the best suited to it. The numerical experiments aimed on forecasting the 24-element vector of hourly load of the power system in Poland have confirmed the superiority of the presented approach. The quality measures of forecast have been significantly improved.
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