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Cobiss

Thermal Science 2020 Volume 24, Issue 6 Part A, Pages: 3795-3806
https://doi.org/10.2298/TSCI191207474Z
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Experimental validation of wind energy estimation

Živković Predrag M. ORCID iD icon (University of Niš, Faculty of Mechanical Engineering, Niš, Serbia), pzivkovic@masfak.ni.ac.rs
Tomić Mladen A. ORCID iD icon (University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia)
Bakić Vukman V. ORCID iD icon (University of Belgrede, Vinca Institute of Nuclear Science, Belgrade, Serbia)

Wind power assessment in complex terrain is a very demanding task. Modeling wind conditions with standard linear models does not sufficiently reproduce wind conditions in complex terrains, especially on leeward sides of terrain slopes, primarily due to the vorticity. A more complex non-linear model, based on Reynolds averaged Navier-Stokes equations has been used. Turbulence was modeled by modified two-equations k-ε model for neutral atmospheric boundary-layer conditions, written in general curvelinear non-orthogonal co-ordinate system. The full set of mass and momentum conservation equations as well as turbulence model equations are numerically solved, using the as CFD technique. A comparison of the application of linear model and non-linear model is presented. Considerable discrepancies of estimated wind speed have been obtained using linear and non-linear models. Statistics of annual electricity production vary up to 30% of the model site. Even anemometer measurements directly at a wind turbine’s site do not necessarily deliver the results needed for prediction calculations, as extrapolations of wind speed to hub height is tricky. The results of the simulation are compared by means of the turbine type, quality and quantity of the wind data and capacity factor. Finally, the comparison of the estimated results with the measured data at 10, 30, and 50 m is shown.

Keywords: wind turbine, modeling, CFD, combined methodology, measurement

Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR33036