Using field data–based large eddy simulation to understand role of atmospheric stability on energy production of wind turbines

Abstract

A novel and a robust high-fidelity numerical methodology has been developed to realistically estimate the net energy production of full-scale horizontal axis wind turbines in a convective atmospheric boundary layer, for both isolated and multiple wind turbine arrays by accounting for the wake effects between them. Large eddy simulation has been used to understand the role of atmospheric stability in net energy production (annual energy production) of full-scale horizontal axis wind turbines placed in the convective atmospheric boundary layer. The simulations are performed during the convective conditions corresponding to the National Renewable Energy Laboratory field campaign of July 2015. A mathematical framework was developed to incorporate the field-based measurements as boundary conditions for the large eddy simulation by averaging the surface flux over multiple diurnal cycles. The objective of the study is to quantify the role of surface flux in the calculation of energy production for an isolated, two and three wind turbine configuration. The study compares the mean value, +1 standard deviation, and −1 standard deviation from the measured surface flux to demonstrate the role of surface heat flux. The uniqueness of the study is that power deficits from large eddy simulation were used to determine wake losses and obtain a net energy production that accounts for the wake losses. The frequency of stability events, from field measurements, is input into the calculation of an ensemble energy production prediction with wake losses for different wind turbine arrays. The increased surface heat flux increases the atmospheric turbulence into the wind turbines. Higher turbulence results in faster wake recovery by a factor of two. The faster wake recovery rates result in lowering the power deficits from 46% to 28% for the two-turbine array. The difference in net energy production between the +1 and −1 standard deviation (with respect to surface heat flux) simulations was 10% for the two-turbine array and 8% for the three-turbine array. An ensemble net energy production by accounting for the wake losses indicated the overestimation of annual energy production from current practices could be corrected by accounting for variation of surface flux from the mean value.

Mechanisms of dynamic near-wake modulation of a utility-scale wind turbine

“…2018; Blaylock et al. 2019; Nielson & Bhaganagar 2019).

Figure 1.( a ) The entire simulation domain, showing the grid refinement and the position of the turbine.

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