Could Crop Height Affect the Wind Resource at Agriculturally Productive Wind Farm Sites?

Abstract

The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length in a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. These considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.

Simulating effects of a wind‐turbine array using LES and RANS

“…In the latter approach, turbulence can be explicitly added by the parameterization [e.g., Fitch et al, 2012], or implicitly generated through the creation of shear within the rotor layer [e.g., Jacobson and Archer, 2012]. These wind-farm models have been used to simulate wake impacts on local hydrometeorology [Baidya Roy, 2011;Fitch et al, 2013a], investigate the aggregate effect of wind power on regional and global climate [Kirk-Davidoff and Keith, 2008;Fiedler and Bukovsky, 2011;Wang and Prinn, 2011;Vautard et al, 2014;Fitch, 2015a], evaluate the sensitivity of wind-farm output to surface characteristics [Vanderwende and Lundquist, 2015], and estimate global wind resources [Lu et al, 2009;Marvel et al, 2013;Jacobson and Archer, 2012;Adams and Keith, 2013].…”

Role of Surface Energy Exchange for Simulating Wind Turbine Inflow: A Case Study in the Southern Great Plains, USA

“…This is because the wind speed profile is sensitive to other factors including the surface drag induced by canopy roughness. For example, in [16] the authors found that differences in the roughness length, z0, from changing the landscape from a corn canopy (zo = 0.25 m) to soybean (zo = 0.10 m) in the Noah LSM, increased hub-height wind speed and decreased wind shear in the U.S. Midwest. As changes in surface roughness affect surface drag, they also saw larger effects on wind shear in the bottom half of the rotor-disk.…”

“…Previous studies have examined the role of surface and subsurface properties on near-surface meteorology and PBL development (e.g., [6][7][8][9][10][11][12][13]), the role of the PBL scheme in WRF for wind forecasting (e.g., [14,15]), and the impact of crop type and surface drag (via the aerodynamic roughness length, zo) on hub-height wind speed and shear [16]. However, few studies have specifically looked at the role of surface energy exchange and LSM choice on rotor-disk wind shear.…”

Development of a High-Resolution Wind Forecast System Based on the WRF Model and a Hybrid Kalman-Bayesian Filter

“…The Weather Research and Forecasting (WRF) meso and microscale model has been used extensively during the last few years in the wind energy field for a variety of applications [8][9][10]. It includes a wind turbine parameterization [11] enabling the study of the wake effect from wind turbines [5,12].…”