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Novel Computational Approach to Enhance Wind Farm Layout

Novel Computational Approach to Enhance Wind Farm Layout

Researchers from University of Denver developed a computational system to examine and improve the operational conditions of a wind turbine

According to Union of Concerned Scientists September 2017 Fact Sheet, in 2008, 51% of the electricity supply in the U.S came from coal and it decreased to 31% by 2016. This in turn has led to public health benefits worth US$ 250 billion from 2008 to 2016. This can be attributed to the trend of energy industry to exploit alternative energy sources. Large wind farms are the most common and profitable applications for wind energy systems. However, large wind farms also face certain drawbacks such as the row arrangement of the generators. Such patterns need large areas of land for rotors.

Now, a team of researchers from University of Denver used velocity wake data from the Model Experiments in Controlled Conditions (MEXICO) experiment to validate a novel simulation. In a previous research, the team recommended safe distances to avoid the wind turbines blade/components damage and output power waste. However, it is necessary to determine the optimal spacing between turbines in a wind farm. In the current research published in the journal MDPI Energies on March 12, 2019, the team validated a wind turbine farm Computational Fluid Dynamics (CFD) simulation.

To describe the three-dimensional velocity flow field in the near wake, the team conducted several different flow field measurements in the MEXICO experiment. The team found that the computational results are identical to the selected experimental data for the radial and axial traverse in axial flow conditions. The team observed minor numerical discrepancies in the experiments. However, according to the researchers, the novel CFD simulation model is efficient in governing the effect of design parameters on the wake aerodynamic behavior. The team implemented each wind farm row to develop a profile from each outlet. The approach allowed to simulate multiple wind turbine rows with comparatively reduced computational resources in terms of processers. According to the researchers, this technique can be used to model wind farm rows while still considering wake interaction effects.

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