An Induction Curve Model for Prediction of Power Output of Wind Turbines in Complex Conditions

Mohsen Vahidzadeh and Corey D. Markfort
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Mohsen Vahidzadeh: IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242, USA
Corey D. Markfort: IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242, USA

Energies, 2020, vol. 13, issue 4, 1-23

Abstract: Power generation from wind farms is traditionally modeled using power curves. These models are used for assessment of wind resources or for forecasting energy production from existing wind farms. However, prediction of power using power curves is not accurate since power curves are based on ideal uniform inflow wind, which do not apply to wind turbines installed in complex and heterogeneous terrains and in wind farms. Therefore, there is a need for new models that account for the effect of non-ideal operating conditions. In this work, we propose a model for effective axial induction factor of wind turbines that can be used for power prediction. The proposed model is tested and compared to traditional power curve for a 2.5 MW horizontal axis wind turbine. Data from supervisory control and data acquisition (SCADA) system along with wind speed measurements from a nacelle-mounted sonic anemometer and turbulence measurements from a nearby meteorological tower are used in the models. The results for a period of four months showed an improvement of 51% in power prediction accuracy, compared to the standard power curve.

Keywords: atmospheric boundary layer; equivalent wind speed; power curve; turbulence; wind power prediction; meteorological tower (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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