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Communication Dans Un Congrès Année : 2015

Solar PV Power Forecasting Using Extreme Learning Machine and Information Fusion

Résumé

We provide a learning algorithm combining distributed Extreme Learning Machine and an information fusion rule based on the ag-gregation of experts advice, to build day ahead probabilistic solar PV power production forecasts. These forecasts use, apart from the current day solar PV power production, local meteorological inputs, the most valuable of which is shown to be precipitation. Experiments are then run in one French region, Provence-Alpes-Côte d'Azur, to evaluate the algorithm performance.
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Dates et versions

hal-01145680 , version 1 (25-04-2015)

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  • HAL Id : hal-01145680 , version 1

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Hélène Le Cadre, Ignacio Aravena, Anthony Papavasiliou. Solar PV Power Forecasting Using Extreme Learning Machine and Information Fusion. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2015, Bruges, Belgium. ⟨hal-01145680⟩
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