We have developed a method specifically for renewable energy to generate accurate and site-specific wind, solar & power forecasts. The forecasts are generated with a local high-resolution atmospheric model tuned with measurements, covering the greater area of interest. Furthermore, we apply the newest assimilation and machine learning technique to include site-specific characteristics of a wind farm and/or different turbine locations in the forecast, such as:
Local environmental conditions and influences
Positioning of wind turbines
Characteristics of turbine locations and influences
The following forecast information is generated for specific turbine locations or the wind farm as a whole:
Power output
Wind speed and direction at hub height
Solar radiation
Air density
Pressure
Temperature
Relative Humidity
Other atmospheric parameters/phenomena like vertical wind shear, temperature inversions, and ramping events can also be provided. We provide detailed weather and oceanographic forecast information to support installation activities and optimize wind farm Operations and Maintenance (O&M).
