Posters

Abstract

The paper aims towards a large scale validation of the novel Bandpass Adjusted Turbulence (BAT) methodology[1] for using measurements from ground-based Wind LiDARs for evaluating turbine suitability assessments through the Mast Equivalent Turbine Load Response, a pivotal step in LiDAR-only turbine suitability assessments, under the current best practices. Through the validations it is revealed that a considerably high-fidelity convergence is achieved in loads computed from met. mast anemometer data and BAT or met. mast equivalent data, by using a Generic BAT model. The research also showed that 10-min avg wind speed and turbulence shows different attributes in Flat sites, as compared to other orographies. This paper showcases the flexibility of the dynamic BAT model by further fine-tuning it to target Flat sites by using a Flat-site-specific BAT model, and in similar process venturing into handling Offshore LiDARs and Floating LiDARs. This research originated from the review of previous researches in the topic, where it was evident that potential methodologies were aiming at correcting wind speed and standard deviation to simply match mast measurements. Having acknowledged the potential of latest LiDAR technologies to accurately estimate the average climatic conditions, the BAT method however aims to fine-tune certain components of 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. The methodology is dynamic and a frequency-based assessment, where it allows some frequencies to pass through and other frequencies to be transformed or adjusted by the aforementioned pre-defined BAT model. The selection of the frequencies for the bandpass is based on the turbine loads response.