Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany
Yngve Heggelund (1) F P Marwan Khalil (2) Chad Jarvis (1)
(1) Christian Michelsen Research, Bergen, Norway (2) GexCon, Bergen, Norway
Poster Award Winner
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Presenter's biographyBiographies are supplied directly by presenters at OFFSHORE 2015 and are published here unedited
Yngve Heggelund is a senior scientist with a PhD in applied mathematics. He has been emplyed in the independent research institute Christian Michelsen Research since 2001. Since 2010 he has been working on models for fast wind farm energy production estimates as part of the work for the Norwegian research centre NORCOWE.
A fast reduced order method for assessment of wind farm layouts
Wake losses limit the power production of wind farms. The annual wind farm wake losses depend on positioning of turbines in relation to each other, i.e. the wind farm layout. There is a need for accurate and fast methods for assessing different layouts. To assess the expected performance of a layout, the method needs to be able to compute the flow field and the wake losses in a wind farm for a range of wind speeds and wind directions.
We adapt and assess model reduction methodology applied to wind farm flow. Model reduction has been successfully applied to other fields, but to our knowledge, this application to wind power is new.
The idea is to formulate the governing equations in a reduced finite dimensional solution space spanned by a set of orthogonal basis modes.
The reduced space is constructed by the method of snapshots combined with Proper Orthogonal Decomposition (POD). The snapshots are produced by running Reynolds Averaged Navier-Stokes (RANS) CFD simulations for different setups with respect to wind conditions and turbine arrangements.
Main body of abstract
The theoretical framework for model reduction of the steady state RANS equations for solving wind farm flow problems will be presented. The method is developed for an interactive wind farm layout assessment tool for offshore or flat terrain. Test cases are used for demonstration, and the results are verified with corresponding flow field solutions from a CFD simulator.
We have previously presented results for test cases of three and six turbines, where downstream turbines could be moved in the crosswind direction. We have also presented the ability to reproduce the multiple wake effect where multiple turbines are placed downstream of each other. The goal is to reproduce the production of the turbines with a sufficient accuracy based on as few CFD simulations as possible for building the reduced space. We have also showed that a setup of 21 turbines is computed in less than a second.
The main topic in this work is to assess the performance of the method for variations of wind speeds and wind direction. CFD simulations of a setup of three turbines for a set of wind speeds is used to build the reduced space for the model reduction. The CFD simulations use a neutrally-stratified ambient flow over a surface with roughness length of 3 cm. The turbines applied in the simulations are of type BONUS 2MW with hub height 64 m and rotor diameter 76 m. The hub height wind speed ranges from 7 m/s to 15 m/s.
The production of the turbines in the test setup is reproduced for hub height wind speeds of 9 m/s and 13 m/s with model reduction using a basis build from CFD simulations of hub height wind speeds of 7 m/s, 11 m/s and 15 m/s with a production discrepancy less than 1 % compared to CFD. With a basis build from simulations with hub height wind speeds of 7 m/s and 15 m/s the production discrepancy between model reduction and CFD for hub height wind speeds of 9 m/s, 11 m/s and 13 m/s is less than 2.5 %.
In this presentation, delegates will learn about:
• A novel method for computation of wind fields in wind farms based on CFD and model reduction
• Verification results of the model reduction method applied to wind farm power production