AWS Truepower today announced important updates and improvements to its Deep-Array Wake Model (DAWM), which was first released in openWind® Enterprise in 2010. Concluding a rigorous validation of plant production and wind data from several projects, AWS Truepower also confirmed that the so-called deep-array wake effect, which results in greater wake losses than predicted by standard wake models, can occur in onshore wind projects. Previous research had clearly established such an effect only for offshore projects.
Researchers in the wind energy community are aware that the current generation of wake models underestimates wake losses in offshore wind projects with multiple rows of turbines. This phenomenon results from the cumulative drag imposed by so-called deep turbine arrays on the planetary boundary layer (PBL), the lowest layer of the atmosphere. However, the jury has been out regarding whether or not the deep-array wake effect significantly impacts onshore projects. AWS Truepower’s validation effort indicates that onshore projects are also susceptible to this issue and should be analyzed using the most up-to-date models.
“With developers planning larger and larger wind projects, it is critical that models estimate wake losses as accurately as possible,” said Michael Brower, Chief Technical Officer at AWS Truepower. “AWS Truepower’s DAWM accomplishes this by representing the cumulative drag induced by individual turbines as internal boundary layers, which grow and merge as they propagate downstream. This approach is both flexible and fast, and allows DAWM to handle arrays of any size and shape.”
AWS Truepower compared DAWM to turbine production and wind data from five on- and offshore wind projects. “We were pleased to learn that, after some modifications, the model behaves in a physically consistent manner across a variety of projects,” said Nicholas Robinson, Director of openWind, who led the research and software development. “The DAWM looks to be generalizing exceptionally well between the two offshore sites as well as doing a good job of capturing the effect that we see in the onshore sites.”
“Our deep array model is fast, transitions smoothly from a handful to any number of turbines and captures the effect we’re seeing in the operational data,” he continued. “The validation results indicate that the DAWM employed in openWind Enterprise captures wake effects in large projects both on- and offshore more accurately than standard wake models.”
Details on the theoretical background, its specific application, and validation can be found in the recently published technical paper,The openWind Deep-Array Wake Model, authored by Chief Technical Officer, Michael Brower and Director of openWind, Nicholas Robinson.
The openWind Deep-Array Wake Model Development and Validation. (Revised: May 2012)