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  1. Abstract

    Impacts from current and future wind turbine (WT) deployments necessary to achieve 20% electricity from wind are analyzed using high resolution numerical simulations over the eastern USA. Theoretical scenarios for future deployments are based on repowering (i.e. replacing with higher capacity WTs) thus avoiding competition for land. Simulations for the contemporary climate and current WT deployments exhibit good agreement with observed electricity generation efficiency (gross capacity factors (CF) from simulations = 45–48%, while net CF for WT installed in 2016 = 42.5%). Under the scenario of quadrupled installed capacity there is a small decrease in system-wide efficiency as indicated by annual mean CF. This difference is approximately equal to that from the two simulation years and may reflect saturation of the wind resource in some areas. WT modify the local near-surface climate in the grid cells where they are deployed. The simulated impact on near-surface climate properties at both the regional and local scales does not increase with increasing WT installed capacity. Climate impacts from WT are modest compared to regional changes induced by historical changes in land cover and to the global temperature perturbation induced by use of coal to generate an equivalent amount of electricity.

     
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  2. The Weather Research and Forecasting (WRF) Model has been extensively used for wind energy applications, and current releases include a scheme that can be applied to examine the effects of wind turbine arrays on the atmospheric flow and electricity generation from wind turbines. Herein we present a high-resolution simulation using two different wind farm parameterizations: 1) the “Fitch” parameterization that is included in WRF releases and 2) the recently developed Explicit Wake Parameterization (EWP) scheme. We compare the schemes using a single yearlong simulation for a domain centered on the highest density of current turbine deployments in the contiguous United States (Iowa). Pairwise analyses are applied to diagnose the downstream wake effects and impact of wind turbine arrays on near-surface climate conditions. On average, use of the EWP scheme results in small-magnitude wake effects within wind farm arrays and faster recovery of full WT array wakes. This in turn leads to smaller impacts on near-surface climate variables and reduced array–array interactions, which at a systemwide scale lead to summertime capacity factors (i.e., the electrical power produced relative to nameplate installed capacity) that are 2%–3% higher than those from the more commonly applied Fitch parameterization. It is currently not possible to make recommendations with regard to which wind farm parameterization exhibits higher fidelity or to draw inferences with regard to whether the relative performance may vary with prevailing climate conditions and/or wind turbine deployment configuration. However, the sensitivities documented herein to the wind farm parameterization are of sufficient magnitude to potentially influence wind turbine array siting decisions. Thus, our research findings imply high value in undertaking combined long-term high-fidelity observational studies in support of model validation and verification.

     
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