The aerodynamic shape of wind- turbine blades generates lift and torque, which is eventually turned into electrical power. Improving a blade’s shape so it captures just a percent or two more would be a significant improvement. One such redesign project shows how Computational Fluid Dynamics (CFD) working in concert with optimizing software can reshape such blades to boost a turbine’s capacity factor.
The design optimization of the blade was carried out in Ansys DesignXplorer (DX), an add-on module for the Ansys finite-element software, an engineering program that allows a range of rapid simulations. It lets engineers find answers to ‘what-if’ questions and understand the relationship between design variables and product performance.
The left profile is from the original design. The original and optimized cross sections appear in the middle. An optimized cross section appears at far right. Small changes produced a big result.
For the study, a blade’s geometry was defined using geometric design parameters (variables which can change in value with every design iteration) within the Ansys Workbench and later input into CFD for a full analysis. Traditionally, a designer would take months to test an array of design parameters on a one-by-one basis. However, the software changes the values of the design parameters based on goals set by the user.
The design explorer module provides several ways to optimize a design, including the Response Surface Method (RSM). This lets users efficiently carry out optimization and probabilistic studies. RSM is based on a large amount of data gathered during a first set of runs called Design of Experiments.
RSM uses a function that best represents the behavior of objectives and constraints within a design space and then implements a direct optimization algorithm that attempts to find a best estimated objective and test it again. This process iterates until the accuracy of the RSM is acceptable, or the best designs found by the process do not improve from one iteration to the next.
The blade geometry was parameterized using 19 design characteristics, parameters that manage the geometry of the blade’s profile sections at different locations. Examples include the maximum thickness, its position, curvature of the profile, and twist of the blade.
More than 500 design points were used to model the continuous behavior of changes in blade design. The software calculated the performances of the blade for each set of the 19 parameters that the user defines. The solution coming from each of these set is a design point. Results were impressive. The CFD-based optimization predicted a gain of 48% in power output.
Optimization initiates an iterative design process. One tack could also have been to optimize the blade profile individually for each stream section and then merge the designs afterwards.
Many design parameters can take a designer months to test on a one-by-one basis. But the same task is made possible in much less time using software such as DX. Setting the right design parameters can lead to huge gains. Optimization offers potentially great gains from characteristic of efficiency to costs with appropriate cost functions.
For this case study, DX provided a significantly better design than the original, increasing power output by 48%. The software offers the possibility to assess, in a more thorough manner, optimized solutions by exporting designs for possible re-meshing and mesh-trends dependency analysis. It is also possible to use DX with other workbench solvers and third party CAD models. WPE
By: Ciro Cannavacciuolo, IDAC, www.idac.co.uk
Filed Under: Software, Turbines
I would be interested to know the details of this case study. Is there any paper ?
We are already evaluating ANSYS software for our wind turbine blade applications.
Hi there. I would contact the company directly or Ciro for this information. Should be able to find their site on a Google search. Thanks for reading!