Abstract
The Midwest US currently is experiencing a large build-out of wind turbines in areas where the nocturnal low-level jet (NLLJ) is a prominent and frequently occurring feature. We describe shear characteristics of the NLLJ and their influence on wind power production. Reports of individual turbine power production and concurrent measurements of near-surface thermal stratification are used to turbine wake interactions and turbine interaction with the overlying atmosphere. Progress in forecasting conditions such as wind ramps and shear are discussed. Finally, the pressure perturbation introduced by a line of turbines produces surface flow convergence that may create a vertical velocity and hence a mesoscale influence on cloud formation by a wind farm.
Highlights
During 2012, the state of Iowa generated almost 25% of all its electricity from wind turbines [1]
We describe shear characteristics of the nocturnal low-level jet (NLLJ) and their influence on wind power production
For winds from the WSW power is enhanced by 25-60% within the north line of turbines and we posit three factors: (1) higher terrain at the north line of turbines, (2) daytime fluxes from land-surface heterogeneities, and (3) high shear within the turbine layer during the decay of the NLLJ may contribute to spatial variations in hub height wind speed [3]
Summary
During 2012, the state of Iowa generated almost 25% of all its electricity from wind turbines [1]. For winds from the WSW power is enhanced by 25-60% within the north line of turbines and we posit three factors: (1) higher terrain at the north line of turbines, (2) daytime fluxes from land-surface heterogeneities, and (3) high shear within the turbine layer during the decay of the NLLJ may contribute to spatial variations in hub height wind speed [3]. Research by our group reported elsewhere [19] focuses on improving the boundary-layer parameterization in WRF by including turbulence anisotropies under highly stable stratification As difficult as it is to make accurate day 2 forecasts, forecasts of ramp events, rapid changes in wind speed that lead to extreme changes in wind power output, are even more challenging. The vertical bars in the data show 95% confidence intervals
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