The following videos, produced through the RADWIND Project, feature subject matter experts providing technical instruction on modeling for wind generation projects. Each video is about 20 minutes long: COMMERCIAL WIND PROJECT ASSESSMENT USING WEATHER MODELS:
Mark Stoelinga, PhD - Lead, Atmospheric Science Innovation and Applications, ArcVera Renewables
Mark Stoelinga is a widely recognized expert mesoscale meteorology and numerical weather prediction with a demonstrated history of success and expertise in meteorological research and applications to renewable energy. Mark's skills in numerical weather prediction, technical writing, and wind energy have allowed him to distinguish himself in his field. He has worked on development and validation of many aspects of wind energy assessment and forecasting including remote sensing measurement systems, wake modeling, time series energy assessment, seasonal wind resource forecasting, and solar energy forecasting.
Mark's video, to set the context for a desktop modeling approach, first introduces the steps of a commercial wind resource assessment campaign for wind resource assessment. His presentation then focuses on the modeling approach, which is based on a series of physics-based, nested weather and wind flow models to bring global weather models down to the project scale, and describes the importance of weather models as an essential component of a high-quality approach.
MODELING TO REDUCE THE TIME FOR CHARACTERIZING WIND RESOURCES
Robert Sunderland, Managing Director, Digital Engineering
Robert Sunderland has, over nearly twenty years, honed his expertise in analytics, weather modeling, and technology transfer. His work at Digital Engineering has focused on delivering innovative, scalable, wind resource estimation methods that have directly enabled the development of nearly 40 MW of distributed wind. Digital Engineering's pioneering methods have supported hundreds of projects spanning Europe, Australia, and the Americas.
Robert's video introduces the concept a modeling approach to wind resource assessment as a means to reducing the time needed to characterize the wind resource at a site without sacrificing accuracy. The video describes a nested weather model process with the addition of computational fluid dynamics models to account for the effect of ground-level obstructions; an addition which is important when working with smaller wind turbines with lower hub heights.