A numerical framework for optimal trade-offs between land use and LCOE using efficient, blockage-aware multi-fidelity methods

Abstract. This paper introduces a novel approach to efficiently estimate the annual energy production (AEP) of a wind farm. The numerical predictions are generated thanks to a multi-fidelity model that combines a classical low-fidelity wake engineering solver with a mid-fidelity computational fluid dynamic solver. The novel setup is not only faster than conventional approaches but is also capable of estimating the AEP of tightly spaced wind farms. Using this approach, we explore the trade-off between land use and levelized cost of energy (LCOE) for a wind farm made of 25 turbines. The results of this study, which ignore impact the layout sensitivity of fatigue loads and their incumbent effect on costs, quantify the penalty on LCOE performance that can be paid to restrict the land use of a wind farm. The results also exhibit the novel capabilities of our approach for multi-fidelity wind farm design to avoid false optima according to incomplete representations of the relevant physical phenomena.