The Jensen wind farm parameterization

نویسندگان

چکیده

Abstract. Wind farm power production is known to be significantly affected by turbine wakes. When mesoscale numerical models are used predict production, the wakes cannot resolved directly because they sub-grid features, and therefore their effects need parameterized. Here we propose a new wind parameterization that based on Jensen model, well-known analytical wake model predicts expansion speed of an ideal wake. The implemented inserted into two commonly atmospheric models: Weather Research Forecasting (WRF) (herein referred as just “WRF”) Model for Prediction Across Scales (MPAS). In addition, internal variability in direction within farm, uncertainty, superposition multiple taken account with innovative approach. proposed approach tested against observational data at offshore farms: Lillgrund (small size tightly spaced) Anholt (large widely spaced). Results indicate predicted more accurately than Fitch parameterization, which only one available WRF. Power predictions similar WRF MPAS. sensitivity grid resolution small, bias generally low negative. conclusion, recommend MPAS, especially coarse resolution, high density, directions aligned columns.

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ژورنال

عنوان ژورنال: Wind energy science

سال: 2022

ISSN: ['2366-7451', '2366-7443']

DOI: https://doi.org/10.5194/wes-7-2407-2022