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

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

8. Forecasting intrahourly variability of wind generation

9. Characterisation of forecast errors and benchmarking of renewable energy forecasts

10. Renewable forecasting and electricity markets

11. Forecasting for the estimation of reserves into power systems

12. Forecasting for storage management

13. Dynamic line rating forecasting

14. The role of predictability in the investment phase of wind farms

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.