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Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices
2019
Applied Energy
The availability of accurate day-ahead energy prices forecasts is crucial to achieve a successful participation to liberalized electricity markets. Moreover, forecasting systems providing prediction intervals and densities (i.e. probabilistic forecasting) are fundamental to enable enhanced bidding and planning strategies considering uncertainty explicitly. Nonetheless, the vast majority of available approaches focus on point forecast. Therefore, we propose a novel methodology for probabilistic
doi:10.1016/j.apenergy.2019.05.068
fatcat:vfer6r7hfve3rmj6ymqcmkq6um