technology & engineering > power resources / alternative & renewable
Renewable Energy Forecasting: From Models to Applications
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Renewable Energy Forecasting: From Models to Applications 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. The final part of the book focuses on important applications of forecasting for power system management and in energy markets.
Due to shrinking fossil fuel reserves and concerns about climate change, renewable energy holds an increasing share of the energy mix. Solar, wind, wave, and hydro energy are dependent on highly variable weather conditions, so their increased penetration will lead to strong fluctuations in the power injected into the electricity grid, which needs to be managed. Reliable, high quality forecasts of renewable power generation are therefore essential for the smooth integration of large amounts of solar, wind, wave, and hydropower into the grid as well as for the profitability and effectiveness of such renewable energy projects.
Kariniotakis, Georges: - George Kariniotakis received his Eng. and M.Sc. degrees from Greece in 1990 and 1992 respectively, and his Ph.D. degree from Ecole des Mines de Paris in 1996. He is currently with the Centre PERSEE of MINES ParisTech in France as a senior scientist and head of the Renewable Energies and Smartgrids Group. He has authored more than 200 scientific publications in journals and conferences. He has been involved as participant or coordinator in more than 40 R&D projects in the fields of renewable energies and distributed generation. Among them, he was the coordinator of some major EU projects in the field of wind power forecasting such as Anemos, Anemos.plus and SafeWind projects. His scientific interests include among others timeseries forecasting, decision making under uncertainty, modelling, management and planning of power systems.
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