Factors Impacting Projected Annual Energy Production from Offshore Wind Farms on the US East and West Coasts

Rebecca J. Barthelmie (), Kelsey B. Thompson and Sara C. Pryor
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Rebecca J. Barthelmie: Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853, USA
Kelsey B. Thompson: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14853, USA
Sara C. Pryor: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14853, USA

Energies, 2025, vol. 18, issue 15, 1-34

Abstract: Simulations are conducted using a microscale model framework to quantify differences in projected Annual Energy Production (AEP), Capacity Factor (CF) and wake losses for large offshore wind farms that arise due to different input datasets, installed capacity density (ICD) and/or wake parameterizations. Differences in CF (and AEP) and wake losses that arise due to the selection of the wake parameterization have the same magnitude as varying the ICD within the likely range of 2–9 MW km −2 . CF simulated with most wake parameterizations have a near-linear relationship with ICD in this range, and the slope of the dependency on ICD is similar to that in mesoscale simulations with the Weather Research and Forecasting (WRF) model. Microscale simulations show that remotely generated wakes can double AEP losses in individual lease areas (LA) within a large LA cluster. Finally, simulations with the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model are shown to differ in terms of wake-induced AEP reduction from those with the WRF model by up to 5%, but this difference is smaller than differences in CF caused by the wind farm parameterization used in the mesoscale modeling. Enhanced evaluation of mesoscale and microscale wake parameterizations against observations of climatological representative AEP and time-varying power production from wind farm Supervisory Control and Data Acquisition (SCADA) data remains critical to improving the accuracy of predictive AEP modeling for large offshore wind farms.

Keywords: annual energy production; capacity factor; COAWST; mesoscale; offshore wind energy; PyWake; simulations; uncertainty; wake losses; wakes; wind farm; wind turbine; WRF (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: 2025
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