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Renewable energy forecasting : from models to applications /

This book provides an overview of the state-of-the-art of renewable energy forecasting technology and its applications. After an introduction to the principles of meteorology and renewable energy generation, groups of chapters address forecasting models, very short-term forecasting, forecasting of e...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Kariniotakis, Georges (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Duxford, United Kingdom : Woodhead Publishing, an imprint of Elsevier, [2017]
Colección:Woodhead Publishing in energy.
Temas:
Acceso en línea:Texto completo

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245 0 0 |a Renewable energy forecasting :  |b from models to applications /  |c edited by George Kariniotakis. 
264 1 |a Duxford, United Kingdom :  |b Woodhead Publishing, an imprint of Elsevier,  |c [2017] 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Woodhead Publishing Series in Energy 
504 |a Includes bibliographical references and index. 
588 0 |a Online resource; title from PDF title page (EBSCO, viewed June 27, 2017) 
505 0 |a Front Cover; Renewable Energy Forecasting; Related titles; Renewable Energy ForecastingWoodhead Publishing Series in EnergyFrom Models to ApplicationsEdited ByGeorge Kariniotakis?; Copyright; Contents; List of contributors; One -- Introduction to meteorology and measurement technologies; 1 -- Principles of meteorology and numerical weather prediction; 1.1 Introduction to meteorology for renewable energy forecasting; 1.1.1 Atmospheric motion; 1.1.2 Prediction across scales; 1.1.3 Atmospheric chaos; 1.2 Observational data and assimilation into numerical weather prediction models 
505 8 |a 1.2.1 Observational data1.2.2 Data assimilation; 1.2.2.1 Nudging; 1.2.2.2 Variational assimilation; 1.2.2.3 Ensemble Kalman filters; 1.2.2.4 Hybrid approaches; 1.2.3 Coupled models; 1.3 Configuring numerical weather prediction to the needs of the problem; 1.3.1 Fundamentals of numerical weather prediction; 1.3.1.1 Dynamic solver; 1.3.1.2 Parameterizations; 1.3.2 Standard physics available in numerical weather prediction models; 1.3.3 Configuration of numerical weather prediction models for specific applications; 1.3.4 Model development: the WRF-Solar model; 1.4 Postprocessing 
505 8 |a 1.5 Probabilistic forecasting1.6 Planning for validation; 1.7 Weather forecasting as a Big Data problem; Acknowledgments; References; Further reading; 2 -- Measurement methodologies for wind energy based on ground-level remote sensing; 2.1 Introduction; 2.1.1 Historical background; 2.1.2 Measuring principles for a heterodyne wind lidar; 2.1.3 Wind lidar calibration; 2.1.4 Climatological use of Doppler wind lidar measurements; 2.1.5 Turbulence estimated from wind lidar measurements; 2.1.5.1 Filtering of the signal and its consequence for the estimation of turbulence 
505 8 |a 2.1.5.2 A numerical turbulence reconstruction method from Doppler lidar measurements2.1.5.3 Turbulent properties from a vertically pointing Doppler lidar; 2.1.5.4 Wind gusts from a lidar; 2.1.6 Boundary layer depth detection from lidars; 2.1.7 Long-range and short-range WindScanner systems; 2.1.7.1 The long-range WindScanner system; 2.1.7.2 The short-range WindScanner system; References; Two -- Methods for renewable energy forecasting; 3 -- Wind power forecasting-a review of the state of the art; 3.1 Introduction; 3.1.1 Forecast timescales; 3.1.2 The typical model chain; 3.2 Time series models 
505 8 |a 3.2.1 Time series models for very-short-term forecasting3.2.2 An explanation of the time series model improvements; 3.3 Meteorological modeling for wind power predictions; 3.3.1 Improvements in NWP and mesoscale modeling; 3.3.2 Ensemble Kalman filtering; 3.4 Short-term prediction models with NWPs; 3.4.1 Modeling wind speed versus wind power; 3.5 Upscaling models; 3.6 Spatio-temporal forecasting; 3.7 Ramp forecasting; 3.8 Variability forecasting; 3.9 Uncertainty of wind power predictions; 3.9.1 Statistical approaches; 3.9.2 Ensemble forecasts, risk indices, and scenarios 
520 |a This book provides an overview of the state-of-the-art of renewable energy forecasting technology and its applications. After an introduction to the principles of meteorology and renewable energy generation, groups of chapters address forecasting models, very short-term forecasting, forecasting of extremes, and longer term forecasting. 
650 0 |a Renewable energy sources  |x Forecasting. 
650 6 |a �Energies renouvelables  |0 (CaQQLa)201-0018247  |x Pr�evision.  |0 (CaQQLa)201-0380155 
650 7 |a TECHNOLOGY & ENGINEERING  |x Power Resources  |x Alternative & Renewable.  |2 bisacsh 
650 7 |a Renewable energy sources  |x Forecasting  |2 fast  |0 (OCoLC)fst01094581 
700 1 |a Kariniotakis, Georges,  |e editor. 
776 0 8 |i Print version:  |t Renewable energy forecasting.  |d Duxford, United Kingdom : Woodhead Publishing, an imprint of Elsevier, [2017]  |z 9780081005040  |z 0081005040  |w (OCoLC)960845109 
830 0 |a Woodhead Publishing in energy. 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780081005040  |z Texto completo