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Delegates are invited to meet and discuss with the poster presenters in this topic directly after the session 'The model chain: First steps towards tomorrow's technology' taking place on Thursday, 13 March 2014 at 09:00-10:30. The meet-the-authors will take place in the poster area.

Arne R. Gravdahl WindSim AS, Norway
Co-authors:
Arne Reidar Gravdahl (1) F P Catherine Meissner (1) Christopher Nunalee (2)
(1) WindSim AS, Tonsberg, Norway (2) North Carolina State University, Raleigh NC, United States

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Abstract

From reanalysis data to park optimization

Introduction

The extraordinary surge in wind energy development over the past two decades has been accelerated by the abundance of locations with promising wind resources. These locations have been aggressively sought-out due to their low-risk of inefficiency; nevertheless, as the availability of such sites continues to dwindle, future development depends on the exploration of higher-risk wind complex terrain resource areas. These higher-risk sites are inevitably more sensitive to pre-construction layout design and accurate wind resource characterization. This presentation comment on the importance of optimizing turbine positions while quantifying potential Annual Energy Production (AEP) improvements for a number of existing wind farms.

Approach

The objective of this study is to quantitatively understand how AEP can be optimized through high-resolution wind turbine micro-siting. We couple 3D CFD simulation output with an optimization algorithm to compare the AEP of existing wind farm layouts against optimized configurations. Limiting factors inherent to the local wind climatology, as defined by the IEC standards, are incorporated.

Main body of abstract

The objective of this study is to quantitatively understand how potential wind farm AEP can be optimized through high-resolution wind turbine micro-siting. The procedure consists of three steps i) establishing the local climate based on reanalysis data, ii) establish the local wind fields based on CFD simulations and iii) optimizing the layout incorporating the IEC constraints. Original and optimized turbine layouts are presented for 7 sites around the globe.
Modeled meteorological data from NASA’s “Modern-Era Retrospective analysis for Research and Applications“ (MERRA) reanalysis dataset was used to scale CFD simulations. The major components of the downscaling procedure includes, multiple MERRA grid points, height correction is applied to each MERRA grid point to improve wind speed representativeness and finally horizontally stretched grid is required in the region close to each MERRA point to minimize erroneous terrain speed-up near climatology point.
We couple CFD simulation output with an optimization algorithm to compare the AEP of existing wind farm layouts against optimized configurations. Limiting factors inherent to the local wind climatology, as defined by the International Electrotechnical Commission (IEC) standards, are incorporated. Our findings highlight the advantages of early-stage site analysis as the industry moves towards development in higher-risk wind regimes.
For the case investigated, the park optimization process increased the AEP of primarily 3 to 10%, with an outlier of 32%. The wake loss decrease was up to 7%.


Conclusion

We coupled CFD simulation output with an optimization algorithm to compare the AEP of existing wind farm layouts against optimized configurations. For the case investigated, the park optimization process increased the AEP of primarily 3 to 10%, with an outlier of 32%. The wake loss decrease was up to 7%. Our findings highlight the advantages of advanced site analysis at an early stage.


Learning objectives
The audience will learn about the added value of CFD based park optimization, how wake losses and IEC criteria should be incorporated into the optimization of the turbine layout. Finally the audience will learn about the performance increase of wind parks achievable by early stage park optimization.