Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.
Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
Arne Reidar Gravdahl (1) F Catherine Meissner (1) Nikos Frouzak (1)
(1) WindSim AS, Tønsberg, Norway
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Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
Arne Gravdahl holds a Ph.D in Turbulence modelling from The Norwegian Institute of Technology in Trondheim. For more than 20 years he has been working within the area of Computational Fluid Dynamics, CFD. Today he is the CTO in WindSim AS, a software company developing the simulator WindSim. WindSim is used within the wind energy sector for optimizing the energy production from wind farms.
PosterDownload poster (11.38 MB)
Downscaling Merra mesoscale data for calculating the annual energy production of Norwegian wind farms
For many wind farm developers, obtaining meteorologically representative and accurate wind climatology data proves to be one of the most challenging aspects of their wind resource assessment campaign. As an alternative to the conventional technique of deploying multiple tall met masts and waiting several years for this data, we propose the use of mesoscale reanalysis model output statistically and dynamically downscaled using computational fluid dynamics (CFD).
In the proposed methodology, we use long term global mesoscale reanalysis data from NASA’s “Modern-Era Retrospective analysis for Research and Applications“ (MERRA) reanalysis dataset to scale CFD simulations, of varying complexity, in order to generate wind (speed and direction) time series comparable to those measured by met mast sensors. These ‘synthetic’ wind time series primarily rely on (1) accurate CFD simulations and (2) properly defined forcing data from the mesoscale model. Incorporating mesoscale reanalysis data into the wind resource assessment process offers a number of unique advantages and opportunities for application which will be discussed in the presentation.
Main body of abstract
The accuracy of this technique is largely sensitive to terrain complexity but wind speed errors of less than approximately ±15% are easily achievable (Nunalee et al. 2014). The obtained wind time series can be used to calculate the annual energy production of nearby wind farms using CFD. Based on reported hourly power production data from 7 Norwegian wind farms the calculated annual energy production of this technique is validated and dependencies between the downscaling technique and the calculated annual energy production will be discussed.
The technique has the potential to be used for a first rough site assessment if no measurement data is available at the site yet. The limit of the proceedure is in areas where the mesoscale wind circulations get very important which cannot be represented by the MERRA.
The audience will learn how to create virtual measurement masts based on MERRA data.
They will learn about the reliability of the presented method and how the method can be used for early screening of potential sites.