April 13, 2022
Despite significant progress in the last decades, global weather forecasts continue to be affected by systematic errors that require corrections. Improving atmospheric forecasting associated with renewable energy production is therefore crucial to integrate energy systems into the power grid to balance supply and demand.
Renewable energy forecasting has progressed towards the development of advanced physical and statistical algorithms to improve the local and probabilistic forecasting ability of global-scale models. To this end, academic and industrial research has developed a rapidly growing collection of down-scaling and post-processing methods. By means of these innovative techniques, WWS offers numerical calibration of local weather forecasts for the planning, design and maintenance of renewable energy projects. In particular, the forecast uncertainty is key for efficient operations.
Our numerical modelling services use the knowledge of a predictive probability distribution for a future quantity (wind, waves, currents and solar radiation) in order to quantify the forecast uncertainty. The image on the right is an example forecast for a specific wind-farm location, and shows the level of accuracy achievable once a detailed calibration is implemented compared with best available model forecasts. Current research by Dr. Andrea Mazzino on calibrated wind predictions can be visualized at this site
We offer Services in the following areas:
Weather hindcast analysis
Site specific, high-resolution deterministic and statistical forecasts for wind, wave, tides and solar radiation
Applications to economic evaluations for new and existing renewable energy projects
Applications to facility operations & energy marketing