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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
Bin Fu Huaneng Renewables Corporation, LTD, China
Co-authors:
CHEN GUO (1) F ZIXIAO JIANG (2) BIN FU (2) XIN XIE (2) CELINE BEZAULT (3)
(1) Huaneng Renewables Corporation, LTD, Beijing, China (2) Meteodyn China, Beijing, China (3) Meteodyn France, Nantes, France

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Presenter's biography

Biographies are supplied directly by presenters at EWEA 2015 and are published here unedited

Bin FU, born in Chang Chun, Jilin Province of China in 1980, obtained a bachelor’s degree in Information Management and Information System from Xi’an Jiaotong University in 2003, and a master’s degree in Management Science from Xi’an Jiaotong University in 2008. He works for Meteodyn as director of East Asia since 2007.


Poster

Poster Download poster (12.01 MB)

Abstract

Use of mesoscale modeling to increase the reliability of wind resource assessment and micro-siting in mountainous areas

Introduction

During wind farm design phase, the wind direction distribution is a crucial information for wind turbine layout optimization. However, in complex terrains, the wind rose at hub height of the wind turbines can be quite different from met mast measurement, due to the terrain effect on the wind flow close to the ground.
A study has been carried out on a wind farm project in mountainous areas in Guangdong province of China. It is observed that the wind direction distributions at 80 m height at the two met masts, which have a horizontal distance of 6 km between them, are quite different. In order to reduce the uncertainty in wind rose prediction at wind turbines, we use mesoscale simulation coupled with CFD microscale model to produce the high resolution wind map and to determine the wind direction distributions at hub height of wind turbines.


Approach

The mesoscale simulation is made with Meteodyn AMP platform based on weather research and forecast (WRF) model and ARW dynamic solver. The computed period is from June 2013 to May 2014. The size of domain is 300 km x 150 km. The grid resolution is 3 km and the time step is 1 hour.
Firstly, the coherence between the wind roses extracted from mesoscale simulation and measured at the met masts has been checked.
Then we use CFD based Meteodyn WT modeling to get a downscaled wind resource map with a spatial resolution of 25 m.
With the high resolution wind map and information on wind direction distributions at different locations on the site, we are able to optimize wind turbine layout.
From mesoscale simulation, it is also possible to extract the wind rose at different heights above the ground, which shows the evolution of the wind direction distribution with height.


Main body of abstract

The wind roses obtained from mesoscale simulation show very good coherence with the measurement. Especially, the mesoscale simulation reproduces well the difference between the wind direction distributions at 80 m height at the two met masts. This difference is probably induced by large scale terrain effect.
The downscaling of mesoscale simulation results is carried out by Meteodyn WT, which takes into account microscale terrain and roughness effects. The resulting high resolution wind map and site-specific wind direction distribution are used for wind turbine layout optimization. Compared to the layout obtained by assuming that the wind roses at the wind turbines are the same as at one of the masts, the optimized layout allows to reduce the loss on AEP and the added turbulence intensity by wake effect.
By observing the wind roses extracted at different heights above the ground, it is also found that, at heights lower than 200 m, the wind direction seems to be significantly affected by the terrain, so the wind roses at hub height at different locations can be quite different; at heights greater than 400 m, we get similar wind roses at different locations.


Conclusion

Mesoscale modeling based on WRF-ARW solver reproduces well the large scale terrain effect on the wind direction distribution in this case of complex mountainous terrains.
In complex terrains, the use of mesoscale modeling provides a complement to met mast measurement. It allows to better determine the turbine-specific wind rose and to reduce the uncertainty in wind resource assessment.
The coupling of mesoscale and CFD model allows to produce high resolution wind map, by taking into account both mesoscale and microscale terrain effects.



Learning objectives
To learn about the methodology of using mesoscale simulation results to improve the wind resource assessment, especially to better evaluate the turbine-specific wind direction distribution through a real case in complex terrains.
To learn about the effect that complex terrains can have on the wind direction distributions at different heights above ground.