09:00 - 10:30 Advanced modeling of offshore and stratified flow
In this session on advanced flow modelling focus will be on the following issues: modelling flow under stable atmospheric conditions, tools for offshore wind farm planning and the benefits of high-resolution modelling. The stable flows will be modelled with CFD codes in three different ways, applied to on-shore and coastal environments.
Delegates will be able to explain:
- why flow under stable conditions is different from neutral flow
- the main additions to the CFD codes in order for the models to improve results under stable conditions
- the main parts of a tool for offshore wind farm planning and how they work together
- how increasing the resolution of models for resource assessment improves the value of the output
Lead Session Chair:
Lars Landberg, DNV-GL, Denmark
James Bleeg (1) F Jean-Francois Corbett (1) Ulrik Horn (1) Richard Whiting (1) Dnyanesh Digraskar (1)
(1) DNV GL, Bristol, United Kingdom
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Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
James Bleeg is a Principal Researcher at DNV GL, where he has worked since 2008. He previously worked for 10 years in the Flow Prediction group at Pratt & Whitney aircraft engines. James studied mechanical and aerospace engineering at Cornell University and the University of Texas at Austin. Presently, his work focuses on the development and validation of CFD-based tools for wind energy applications.
Modelling stability at microscale, both within and above the atmospheric boundary layer, substantially improves wind speed predictions
Despite recent advances, wind flow modelling remains one of the largest sources of uncertainty for pre-construction wind energy production assessments. Many have correctly pointed to atmospheric stability and its absence from some of the most widely used microscale models as a primary cause of significant discrepancies between wind speed predictions and observations in the field. How and to what degree atmospheric stability influences the wind resource is not well understood, however. Nor is there consensus on how to implement stability into a microscale wind flow model. Using a combination of modelling and measurements, this presentation will identify which aspects of atmospheric stability have the most influence on the spatial variation of the wind resource and how these aspects should be accounted for within a microscale wind flow analysis.
Using the shallow Boussinesq approach, we added gravity/buoyancy terms to the governing equations of a steady-state computational fluid dynamics (CFD) model. These terms allow for the modelling of atmospheric stability through application of boundary conditions that are representative of the local conditions at a given site. These boundary conditions can also be tailored to include or neglect various types of atmospheric stability, such as the stable boundary layer, the neutral boundary layer, capping inversions, and stable stratification above the inversion. We applied this model to idealized topographies as well as to operating and prospective wind farms in Sweden, Poland, France, and the UK. The results were interrogated and compared with on-site measurements and energy production data in order to understand how different aspects of atmospheric stability affect the spatial variation of the wind resource.
Main body of abstract
Pre-construction measurements taken at the sites in Poland, France, and Sweden reveal pronounced diurnal trends in the wind speed ratios between measurement locations. When the diurnal variation of static stability within the atmospheric boundary layer (ABL) is accounted for within the CFD wind flow model, these trends can be largely reproduced. Modelling and measurements also indicate that the capping inversion and stable stratification above it have a marked impact on the spatial variation of the wind resource. Stratification above the ABL influences the thickness of the ABL. In other words, it restricts and controls the area through which the boundary layer fluid flows, which in turn can have a first-order impact on how wind speed varies over topography, particularly in complex terrain. Comparisons of CFD results with measurements and production data show that accounting for atmospheric stability within the ABL as well as above the ABL reduces wind speed prediction errors by more than half relative to microscale models that do not account for these key influences.
Modelling and measurements show that stratification within and above the atmospheric boundary layer have a significant impact on the spatial variation of the wind resource. Without accounting for these controlling physics, it is not possible for a microscale wind flow model to consistently produce accurate wind speed predictions. Validation shows, however, that atmospheric stability can be effectively accounted for within a steady-state, microscale CFD model, allowing for the generation of reliable wind speed predictions within the time frame of a typical energy production assessment.
1) How and to what degree stability in the free atmosphere affects the spatial variation of the wind resource—impact quantified using both simulation and measurement.
2) How and to what degree stability within the boundary layer affects the spatial variation of the wind resource—impact quantified using both simulation and measurement
3) The key physical influences that must be accounted for within a wind-farm-scale flow analysis as well as the resolution requirements for such an analysis