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Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms
Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms
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Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms
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Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms
Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms

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Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms
Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms
Journal Article

Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms

2024
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Overview
Calculations of annual energy productions of wind farms are normally very computing demanding as they require simulations of the wind flow field inside the wind farms for a range of ambient wind conditions and directions. Although there exists many advanced computing tools for atmospheric flows, which, in principle, cope with all flow situations, most wind power developers rely their work on simplified engineering models based on analytical approaches and superposition of the flow behind a single row of wind turbines. An alternative to wake modeling is the fully developed wind farm array boundary layer model, which assumes that the wind farm is so large, that the wind field inside the wind farm is in equilibrium with the flow field of the ambient atmospheric boundary layer. Such a model was recently further developed by the authors using a simple correction for coping with finite-sized wind farms. The purpose of the present work is to extend further the finiteness correction formula and validate the model by comparing results to actual production data and to results from other simulation models, such as the Jensen, Gaussian and TurbOPark engineering models. In spite of the simplicity of the proposed model, it outperforms the other models, achieving results within 5% accuracy as compared with full-scale data from existing wind farms.