Posters

Abstract

Market dynamics requires faster and more aggressive blade design that often includes subcomponents such as serrations, or power boost devices. As a consequence, the trade-off between time and accuracy has become more challenging. While classical blade modelling does not consider subcomponents, the increased uncertainty will penalize the design unless expensive simulations are carried out, which slow down the blade design process. Anticipating this, a comprehensive set of aerodynamic and acoustic tools have been developed, in order to capture measured turbine blade performance with lower uncertainty. Leveraging both wind tunnel and turbine field data, tool improvements have demonstrated better match with measurements while keeping rigorous physical modelling. Having the capability to model blade subcomponent into the design from the beginning allows reducing uncertainty, which translates into performance increase. And there is a second benefit: each subcomponent can also be optimized, adding extra performance. The resulting effect is about 1 dBA noise reduction thanks to the advanced acoustic package, and as much as 2% Levelized Cost of Energy (LCoE) reduction by leveraging the improved aerodynamic design tools.