Presentations

Abstract

The research focusses on a novel methodology for using measurements from only Wind LiDARs for turbine loads evaluation, a pivotal step in site suitability assessments. From the literature review, many potential methodologies aim at correcting wind speeds by different methods. This research targets some of the most crucial parameters for wind turbine site-ability, specifically from the perspective of turbine loads response – namely turbulence and spread of the turbulence. This methodology is being actively researched and discussed in the Site Suitability Sub-group of the Consortium For Advancing Remote Sensing (CFARS). The research acknowledges the potential of latest LiDAR technologies to accurately estimate the average climatic conditions and takes advantage of the same to fine-tune the turbulence and its spread, as measured by the LiDAR, to arrive at equivalent turbine loads – as would have been observed with data from a hypothetical met mast anemometer measurement; in other words, a Met Mast Equivalent Turbine Load Response. This novel research inputs 10-min average wind speed and turbulence measurements from LiDAR, transforms the data using a pre-defined model and pursues Met Mast Equivalent Turbine Load Response evaluation. The pre-defined model is prepared from climatic information from a large set of met mast and LiDAR pairs. The methodology is dynamic and takes advantage of the wind turbulence spectra from the LiDAR measurements, for a frequency-based assessment. The algorithm then allows some frequencies to pass through and other frequencies to be transformed or adjusted by the aforementioned pre-defined model – making it a Bandpass Adjusted Turbulence (BAT). The selection of the frequencies for the bandpass is based on the turbine response. This methodology refrains from correction of LiDAR data, and assumes through previous study that LiDAR and the post-processing, together with the advancement technology and research in the area, is equipped to measure and estimate average wind characteristics, and simply adjusts the turbulence and its spread, based on deterministic information, to find a Met Mast Equivalent Turbine Load Response evaluated under the industry standards and best practices. This paper aims to present the methodology and some case studies, among the large validatory sites studied, across the entire world.