Browsing by Author "Manero Font, Jaume"
Now showing items 1-8 of 8
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Deep learning architectures applied to wind time series multi-step forecasting
(Universitat Politècnica de Catalunya, 2020-07-14)
Doctoral thesis
Open AccessForecasting is a critical task for the integration of wind-generated energy into electricity grids. Numerical weather models applied to wind prediction, work with grid sizes too large to reproduce all the local features ... -
Deep learning is blowing in the wind. Deep models applied to wind prediction at turbine level
(Institute of Physics (IOP), 2019)
Conference report
Open AccessWind Energy generation depends on the existence of wind, a meteorological phenomena intermittent by nature, with the consequence of generating uncertainty on the availability of wind energy in the future. The grid stability ... -
“Dust in the wind...”, deep learning application to wind energy time series forecasting
(2019-06-21)
Article
Open AccessTo balance electricity production and demand, it is required to use different prediction techniques extensively. Renewable energy, due to its intermittency, increases the complexity and uncertainty of forecasting, and the ... -
Forecastability measures that describe the complexity of a site for deep learning wind predictions
(2021-05-29)
Article
Open AccessThe application of deep learning to wind time series for multi-step prediction obtains good results at short horizons. The accuracy of a wind forecast is highly dependent on the specific structure of wind in the specific ... -
Go with the flow: Recurrent networks for wind time series multi-step forecasting
(IOS Press, 2018)
Conference report
Open AccessOne of the ways of reducing the effects of Climate Change is to rely on renewable energy sources. Their intermittent nature makes necessary to obtain a mid-long term accurate forecasting. Wind Energy prediction is based ... -
Predicting wind energy generation with recurrent neural networks
(Springer, 2018)
Conference report
Open AccessDecarbonizing the energy supply requires extensive use of renewable generation. Their intermittent nature requires to obtain accurate forecasts of future generation, at short, mid and long term. Wind Energy generation ... -
RETBOO, consultas booleanas
(1985)
Research report
Open AccessRetrieval sobre un fichero de información bibliográfica mediante expresiones booleanas entre descriptores (campos de información). Basado en un análisis sintáctico SLR sobre una gramática que utiliza como operadores ... -
Wind prediction using deep learning and high performance computing
(Springer, 2021)
Conference report
Restricted access - publisher's policyDeep Learning Convolutional Neural Networks have been successfully used in many applications. Its versatility lies in reducing the number of parameters to train while maintaining or improving the feature representation ...
