Experimental study of a Bayesian method for daily electricity load forecasting |
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Authors: | Derek W. Bunn |
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Affiliation: | Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK |
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Abstract: | The method of Bayesian model discrimination is investigated for the possible contributions it may provide in the area of automatically forecasting the daily electricity demand cycle. A set of differing demand models have probabilities attached to them in such a way that these would be continuously updated with the available data and the actual forecasts obtained as expectations across all the models. Simulation experiments indicate significantly improved forecasting performance over a commonly used rescaling type of approach. Some practical issues in implementation are discussed. |
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