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
Raghavendra Krishnamurthy (1) F Matthieu Boquet (1)
(1) LEOSPHERE, Orsay, France
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Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
Dr. Krishnamurthy completed his PhD from Arizona State University on Applications of scanning Doppler lidar for wind energy applications. He has presented at several AWEA and AMS conference presentations and authored several journal papers, including Wind Energy and BAMS.
PosterDownload poster (10.07 MB)
Cartography and Uncertainty of WINDCUBE V2 with Flow Complexity Recognition (FCR TM): A case study in Europe
The need for accurate Lidar measurements in complex terrains has been gaining increasing interest within the wind energy industry in Europe. Several projects have been deploying vertical Lidar profilers to assess the wind flow behavior in a variety of complex terrains. The measurements from vertical profilers in complex terrain causes increased uncertainty due in-homogeneous flow conditions over the sensing volume. Hence it is very important to know locations where a vertical profiler can be placed and its expected uncertainty at those locations.
The cartography of a particular geographic location is taken into consideration and the terrain complexity is determined based on criteria’s developed at LEOSPHERE. These criteria’s were developed after analyzing terrain variation data sets at several complex sites, where WINDCUBE V2 Lidars were used. The uncertainty estimates at each of these sites were estimated and an expression for uncertainty calculation based on FCR performance and knowledge of the FCR tool will be provided.
Main body of abstract
The use of remote sensing data in complex terrain is questionable due to non-homogeneity of winds over the sensing volume, and to that effect Flow Complexity Recognition (FCR) embedded add-on software was developed to reduce the measurement uncertainty of complex wind conditions from WINDCUBE V2 profilers in moderately complex terrains. Along with the theoretical analysis of the add-on, we have performed a sensitivity analysis of the performance of FCR for various sites around the world and have evaluated the key factors determining the performance of FCR in moderately complex terrains. In this paper, we have evaluated those key factors for European countries and are able to give an estimate of the uncertainty at every location. The terrain sensitivity factors to FCR performance will be shown along with an uncertainty scheme based on historic knowledge of FCR performance and description of the algorithm key steps. The uncertainty is calibrated based on the knowledge of uncertainty estimated in similar terrain conditions for different sites around the world. Finally, uncertainty maps for European countries and expected FCR performance will be provided. Cartographic maps of FCR performance and uncertainty over a geographic area would assist developers and consultants to plan their campaign and pre-evaluate the performance of WINDCUBE V2 measurement accuracy and improvement with FCR option.
The cartography of the FCR performance will aid wind farm developers and consultants in assessing location of WINDCUBE V2 profilers with FCR prior to deployment at a site and get an understanding of the expected uncertainty at those locations. The key steps and performance indices of the FCR software will allow a better understanding of its performance in moderately complex sites.
1. How to evaluate FCR performance and uncertainty
2. Get knowledge about WINDCUBE V2 with FCR algorithm
3. New uncertainty estimation methodology from prior estimates for a geographic location in Europe