RENEWABLE ENERGY FORECASTING

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.

Autorentext
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.

Klappentext

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.

Inhalt

Part I: Introduction to meteorology and measurement technologies

1. Principles of meteorology and numerical weather forecasting

2. Measurement methodologies for wind energy based on ground-level remote sensing Part II: Methods for Renewable Energy Forecasting

3. Wind energy forecasting models

4. Mathematical Methods for Optimized Solar Forecasting

5. Solar power forecasting based on sky cameras

6. Short term solar power forecasting based on satellite images 7. Wave energy forecasting models

7. Forecasting intrahourly variability of wind generation

8. Characterisation of forecast errors and benchmarking of renewable energy forecasts ** Part III: Applications of forecasting to power system management and markets

   **10. Renewable forecasting and electricity markets

9. Forecasting for the estimation of reserves into power systems

10. Forecasting for storage management

11. Dynamic line rating forecasting
12. The role of predictability in the investment phase of wind farms