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A Minimalistic Prediction Model to Determine Energy Production and Costs of Offshore Wind Farms

Author

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  • Jens Nørkær Sørensen

    (DTU Wind Energy, Aero- and Fluid Dynamics, 2800 Lyngby, Denmark)

  • Gunner Christian Larsen

    (DTU Wind Energy, Response, Aero-elasticity, Control and Hydrodynamics, 4000 Roskilde, Denmark)

Abstract

A numerical framework for determining the available wind power and associated costs related to the development of large-scale offshore wind farms is presented. The idea is to develop a fast and robust minimal prediction model, which with a limited number of easy accessible input variables can determine the annual energy output and associated costs for a specified offshore wind farm. The utilized approach combines an energy production model for offshore-located wind farms with an associated cost model that only demands global input parameters, such as wind turbine rotor diameter, nameplate capacity, area of the wind farm, number of turbines, water depth, and mean wind speed Weibull parameters for the site. The cost model includes expressions for the most essential wind farm cost elements—such as costs of wind turbines, support structures, cables and electrical substations, as well as costs of operation and maintenance—as function of rotor size, interspatial distance between the wind turbines, and water depth. The numbers used in the cost model are based on previous but updatable experiences from offshore wind farms, and are therefore, in general, moderately conservative. The model is validated against data from existing wind farms, and shows generally a very good agreement with actual performance and cost results for a series of well-documented wind farms.

Suggested Citation

  • Jens Nørkær Sørensen & Gunner Christian Larsen, 2021. "A Minimalistic Prediction Model to Determine Energy Production and Costs of Offshore Wind Farms," Energies, MDPI, vol. 14(2), pages 1-27, January.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:2:p:448-:d:481182
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    References listed on IDEAS

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    1. Hasager, C. & Vejen, F. & Bech, J.I. & Skrzypiński, W.R. & Tilg, A.-M. & Nielsen, M., 2020. "Assessment of the rain and wind climate with focus on wind turbine blade leading edge erosion rate and expected lifetime in Danish Seas," Renewable Energy, Elsevier, vol. 149(C), pages 91-102.
    2. Mahdi Abkar & Fernando Porté-Agel, 2013. "The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms," Energies, MDPI, vol. 6(5), pages 1-24, April.
    3. Myhr, Anders & Bjerkseter, Catho & Ågotnes, Anders & Nygaard, Tor A., 2014. "Levelised cost of energy for offshore floating wind turbines in a life cycle perspective," Renewable Energy, Elsevier, vol. 66(C), pages 714-728.
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    1. Rebecca J. Barthelmie & Gunner C. Larsen & Sara C. Pryor, 2023. "Modeling Annual Electricity Production and Levelized Cost of Energy from the US East Coast Offshore Wind Energy Lease Areas," Energies, MDPI, vol. 16(12), pages 1-29, June.

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