Simulation of the Atmospheric Boundary Layer for Wind Energy Applications

Energy production from wind is an increasingly important component of overall/nglobal power generation, and will likely continue to gain an even greater share/nof electricity production as world governments attempt to mitigate climate/nchange and wind energy production costs decrease. Wind energy generation/ndepends on wind speed, which is greatly influenced by local and synoptic/nenvironmental forcings. Synoptic forcing, such as a cold frontal passage,/nexists on a large spatial scale while local forcing manifests itself on a much/nsmaller scale and could result from topographic effects or land-surface heat/nfluxes. Synoptic forcing, if strong enough, may suppress the effects of/ngenerally weaker local forcing. At the even smaller scale of a wind farm,/nupstream turbines generate wakes that decrease the wind speed and increase the/natmospheric turbulence at the downwind turbines, thereby reducing power/nproduction and increasing fatigue loading that may damage turbine components,/nrespectively. Simulation of atmospheric processes that span a considerable/nrange of spatial and temporal scales is essential to improve wind energy/nforecasting, wind turbine siting, turbine maintenance scheduling, and wind/nturbine design./nMesoscale atmospheric models predict atmospheric conditions using observed/ndata, for a wide range of meteorological applications across scales from/nthousands of kilometers to hundreds of meters. Mesoscale models include/nparameterizations for the major atmospheric physical processes that modulate/nwind speed and turbulence dynamics, such as cloud evolution and/nsurface-atmosphere interactions. The Weather Research and Forecasting (WRF)/nmodel is used in this dissertation to investigate the effects of model/nparameters on wind energy forecasting. WRF is used for case study simulations/nat two West Coast North American wind farms, one with simple and one with/ncomplex terrain, during both synoptically and locally-driven weather events./nThe model's performance with different grid nesting configurations, turbulence/nclosures, and grid resolutions is evaluated by comparison to observation data./nImprovement to simulation results from the use of more computationally/nexpensive high resolution simulations is only found for the complex terrain/nsimulation during the locally-driven event. Physical parameters, such as soil/nmoisture, have a large effect on locally-forced events, and prognostic/nturbulence kinetic energy (TKE) schemes are found to perform better than/nnon-local eddy viscosity turbulence closure schemes./nMesoscale models, however, do not resolve turbulence directly, which is/nimportant at finer grid resolutions capable of resolving wind turbine/ncomponents and their interactions with atmospheric turbulence. Large-eddy/nsimulation (LES) is a numerical approach that resolves the largest scales of/nturbulence directly by separating large-scale, energetically important eddies/nfrom smaller scales with the application of a spatial filter. LES allows/nhigher fidelity representation of the wind speed and turbulence intensity at/nthe scale of a wind turbine which parameterizations have difficulty/nrepresenting. Use of high-resolution LES enables the implementation of more/nsophisticated wind turbine parameterizations to create a robust model for wind/nenergy applications using grid spacing small enough to resolve individual/nelements of a turbine such as its rotor blades or rotation area./nGeneralized actuator disk (GAD) and line (GAL) parameterizations are integrated/ninto WRF to complement its real-world weather modeling capabilities and better/nrepresent wind turbine airflow interactions, including wake effects. The GAD/nparameterization represents the wind turbine as a two-dimensional disk/nresulting from the rotation of the turbine blades. Forces on the atmosphere are/ncomputed along each blade and distributed over rotating, annular rings/nintersecting the disk. While typical LES resolution (10-20 m) is normally/nsufficient to resolve the GAD, the GAL parameterization requires significantly/nhigher resolution (1-3 m) as it does not distribute the forces from the blades/nover annular elements, but applies them along lines representing individual/nblades./nIn this dissertation, the GAL is implemented into WRF and evaluated against the/nGAD parameterization from two field campaigns that measured the inflow and/nnear-wake regions of a single turbine. The data-sets are chosen to allow/nvalidation under the weakly convective and weakly stable conditions/ncharacterizing most turbine operations. The parameterizations are evaluated/nwith respect to their ability to represent wake wind speed, variance, and/nvorticity by comparing fine-resolution GAD and GAL simulations along with/ncoarse-resolution GAD simulations. Coarse-resolution GAD simulations produce/naggregated wake characteristics similar to both GAD and GAL simulations (saving/non computational cost), while the GAL parameterization enables resolution of/nnear wake physics (such as vorticity shedding and wake expansion) for high/nfidelity applications./nFor the first time, to our knowledge, this dissertation combines the/ncapabilities of a mesoscale weather prediction model, LES, and high-resolution/nwind turbine parameterizations into one model capable of simulating a real/narray of wind turbines at a wind farm. WRF is used due to its sophisticated/nenvironmental physics models, frequent use in the atmospheric modeling/ncommunity, and grid nesting with LES capabilities. Grid nesting is feeding/nlateral boundary condition data from a coarse resolution simulation to a finer/nresolution simulation contained within the coarse resolution simulation's/ndomain. WRF allows the development of a grid nesting strategy from/nsynoptic-scale to microscale LES relevant for wind farm simulations; this is/ndone by building on the results from the investigation of model parameters for/nwind energy forecasting and the implementation of the GAD and GAL wind turbine/nparameterizations. The nesting strategy is coupled with a GAD parameterization/nto model the effects of wind turbine wakes on downstream turbines at a/nutility-scale Oklahoma wind farm. Simulation results are compared to/ndual-Doppler measurements that provide three-dimensional fields of horizontal/nwind speed and direction. The nesting strategy is able to produce realistic/nturbine wake effects, while differences with the measurements can mostly be/nattributed to the quality of the available weather input data.

Advisor: Chow, Fotini K