Original paper
Towards higher accuracy in wind farm deficit decay modelling – a comparison
Mauz, Moritz; Emeis, Stefan; Hoeckh, Frederick; van Kesteren, Bram; Platis, Andreas; Bange, Jens
Meteorologische Zeitschrift Vol. 32 No. 6 (2023), p. 471 - 486
31 references
published: Dec 5, 2023
published online: Sep 19, 2023
manuscript accepted: Jul 18, 2023
manuscript revision received: Jul 13, 2023
manuscript revision requested: May 30, 2023
manuscript received: Dec 12, 2022
Open Access (paper may be downloaded free of charge)
Abstract
Wind farm wake behaviour and forecasting is gaining the importance recently. It is especially relevant in the German Bight where space for wind farm clusters is limited, and wind farm wake lengths of up to 60 km have been measured. In this investigation newly proposed simple wind farm far-field recovery analytical wake model called SWIFFR is compared to the analytical EFFWAKE ( Emeis, 2010) (Efficiency and Wake) wind farm wake model and the established Frandsen model ( Frandsen et al., 2006). The models in this study are compared to measured in‑situ airborne data, captured during the WIPAFF (wind park far field) project. Three specific flights are shown and compared to the respective model result of each analytical model. The SWIFFR model is derived from the Reynolds-averaged Navier-Stokes equation for the momentum conservation. It describes the wind speed recovery, as for example, in the wake of a wind farm from an atmospheric point of view, by acknowledging turbulent momentum from the atmosphere aloft of the wind farm wake and from the sides as well. A gain in accuracy in comparison to the EFFWAKE model is achieved. Analytical models provide computationally inexpensive results based on some assumptions and simplifications of the governing equations, which distinguishes this approach from purely empirical models.
Keywords
wind energy • off-shore wind farms • wake recovery • airborne measurements • analytical model • turbulence