Posters

Abstract

Wind energy projects rely, despite the need for measurements, on accurate wind flow modeling, particularly within complex terrains where topographical intricacies significantly shape wind patterns. In these cases, the wind field may vary, making it challenging for met masts to represent all the wind flow patterns. Besides complex topography, other meteorological effects may be predominant, requiring special analysis to understand the particular wind flow patterns at the site. Our investigation focuses on the disparities found between two prevalent wind flow modeling approaches: the NOABL code (Phillips, 1979), a mass-dependent model, and mesoscale simulations at a 100-meter resolution based on the Weather and Research Forecast model. Both have been widely and long-used by the industry. In our four sites analysis we conducted detailed analyses specially selected for its complexity. Through the examination of wind but also other meteorological variables at different levels among all the area, we observed significant disparities between the wind flow models employed. Particularly notable was the discrepancy where one model's wind field consistently did not conform to the expected terrain-height relationships. Moreover, our study identified common indicators, such as predominant wind flow directions and temperature fluctuations, suggesting the presence of specific atmospheric phenomena like the Föhn effect and potentially gravitational waves. These findings define a set of conditions for the identification of similar patterns identification. Using this information in early stages can lead to strategic measurement planning in wind energy projects. On the other hand, inadequate measurement data does not allow a correct model performance evaluation, leading to stress in the project. Supplementary measurement campaigns might be necessary to avoid extraordinarily high uncertainty values. Such endeavors inevitably escalate costs and prolong project timelines, complicating project feasibility. Understanding model discrepancies in complex terrains with uncommon but predominant meteorological patterns stands as key knowledge to bring wind flow patterns closer in both initial and later-stage studies of a wind project. We define a set of key signs to be used as an alarm trigger for a site's study. These can be available in a feasibility study's common dataset and would turn the mindset active into finding the most effective strategy for a wind farm feasibility study. Also, designing the wind data correctly for analysis as soon as possible results in a reduced stress of the wind farm design project work.