Prediction and Mitigation of Wind Farm Blockage Losses Considering Mesoscale Atmospheric Response

Leila Legris, Morten Lindholt Pahus, Takafumi Nishino () and Edgar Perez-Campos
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Leila Legris: Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Morten Lindholt Pahus: Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Takafumi Nishino: Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Edgar Perez-Campos: Vestas Wind System A/S, Hedeager 42, 8200 Aarhus, Denmark

Energies, 2022, vol. 16, issue 1, 1-17

Abstract: The engineering wind farm models currently used in industry can assess power losses due to turbine wake effects, but the prediction of power losses due to farm blockage is still a challenge. In this study we demonstrate a new prediction method of farm blockage losses and a possible strategy to mitigate them for a large offshore wind farm in the North Sea, by combining a common engineering wind farm model ’FLORIS’ with the ’two-scale momentum theory’ of Nishino and Dunstan (2020). Results show that the farm blockage losses depend significantly on the ’wind extractability’ factor, which reflects the strength of mesoscale atmospheric response. For a typical range of the extractability factor (assessed using a numerical weather prediction model) the farm blockage losses are shown to vary between about 5% and 15% of the annual energy production (AEP). However, these losses may be mitigated by adjusting turbine operating points taking into account the wind extractability. It is shown that a simple adjustment of the blade pitch angle and tip-speed ratio used below the rated wind speed may increase the AEP by up to about 2%.

Keywords: turbine load control; two-scale momentum theory; wake models; wind extractability; wind farm optimisation; wind resource assessment (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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