Posters

Abstract

Met masts play a crucial role in assessing the energy yield of planned wind farms. While the IEC 61400-50-1 standard provides guidelines for met mast design and operation, the promoted met mast layout with 180° boom orientation and side-by-side anemometry can have limitations in distinguishing upstream and downstream effects. This can impact the accuracy of energy yield assessments, particularly for verifying remote sensing devices (RSDs). To investigate these effects, PAVANA conducted a study on three met masts. These were monitored over several years: one with a 120-meter height that transitioned from a 180° to a 120° boom orientation, and two others with heights of 200 and 160 meters respectively, maintained a 120° and 180° boom orientation. LiDAR devices served as reference sensors. Data was collected across various wind directions and atmospheric conditions. Wind speed and direction measurements were compared between the different boom orientations and the LiDAR data. Statistical analyses were conducted to assess the impact of boom orientation on measurement accuracy and to quantify the reduction in uncertainty. The study revealed that a 120° boom orientation on specifically triangular met masts significantly improves measurement accuracy compared to the traditional 180° arrangement. This is particularly evident in reducing upstream and downstream interference, leading to more reliable wind speed and direction data. Statistical analyses demonstrated a substantial reduction in uncertainty when using the 120° configuration. LiDAR data proved these findings, further validating the superiority of the 120° boom orientation for met mast design. These results have significant implications for wind farm energy yield assessments and RSD verification, emphasizing the importance of adopting the 120° arrangement in future met mast installations. PAVANAs findings demonstrated that adopting a 120° boom orientation on met masts, especially triangular structures, enhances wind resource assessment accuracy. This improves decision-making for site selection and turbine placement, leading to increased project value. The improved data quality enables more precise RSD calibration, supporting their wider adoption. This benefits wind energy by providing more reliable wind data for project development and operations.