Brute force analytical model of wind farm blockage is simplified and improved
Brute force analytical model of wind farm blockage is simplified and improved lead image
In multi-turbine wind farms, each turbine generates a wake that affects the efficiency of the entire farm. A comprehensive analysis of this effect can help maximize a wind farm’s efficiency, preferably before the installation of permanent infrastructure. However, the existing analytical models used for farm design are limited, as they account only for wake effects without considering the influence of the farm’s presence on the upstream region On the other hand, brute force approaches, like numerical models that meticulously simulate each individual turbine and its interactions, are often too computationally costly.
Antonio Segalini calculated upwind wind blockage for a single wind turbine and transformed the results for a cluster of turbines using an analytical model based on linearized Reynolds-averaged Navier-Stokes (RANS) equations. After comparing his results to existing wind tunnel experiments, the linearized approach was proven to be effective for modeling wind farms with different layouts and wind directions.
The simplified model, based on the incompressible linearized RANS equations with constant incoming wind velocity and eddy viscosity, approximates the upwind blockage effect of entire wind farms as linear superpositions of induction zones from each turbine. The method is more computationally efficient than full RANS simulations, while maintaining accuracy comparable to more sophisticated analytical models that use vortex theories.
According to Segalini, companies that do not account for upwind blockage could end up expecting a wind farm to operate at a higher velocity than reality and be surprised by the underproduction of the farm. He hopes his model will help future efforts to develop faster and more accurate assessment tools for the wind energy sector.
Source: “An analytical model of wind-farm blockage,” by A. Segalini, Journal of Renewable and Sustainable Energy (2021). The article can be accessed at http://doi.org/10.1063/5.0046680 .
