Objective and Background:
The purpose of the US DOE’s Mesoscale-Microscale Coupling (MMC) Project is to develop, verify, and validate physical models and modeling techniques that bridge the most important atmospheric scales that determine wind plant performance and reliability. The project seeks to create a new predictive numerical simulation capability that represents a range of dynamic atmospheric flow conditions impacting wind plant performance.
The project approach is to choose case days for which there are observational data for validation. Best-practices studies use data from the flat terrain Scaled Wind Farm Technology site in Texas. For complex terrain cases, the team leverages observational data from the WFIP2 field project in the Pacific Northwest. Science questions include: 1) What is the impact of modeling across the so-called terra incognita, that grid resolution between about 100 m and the boundary layer depth at which numerical artifacts are often difficult to distinguish from physical boundary layer rolls? 2) How to best initialize turbulence at the microscale that was not resolved in the mesoscale model? 3) What is the best way to handle the surface layer parameterizations consistently at the mesoscale and the microscale?
Regarding the terra incognita issue, the team found that 1) the upper range of the terra incognita is roughly the current depth of the boundary layer, 2) using higher resolution for the mesoscale model will produce a smaller fetch in a microscale simulation that contains more turbulent kinetic energy, 3) use of the Lilly turbulence model on the microscale domain results in a higher level of turbulence than parametrized mesoscale schemes, and 4) the microscale results do not vary with the type of turbulence model (PBL schemes or LES closure) used by its parent domain with grid spacing within the terra incognita.
Several turbulence initialization methods have been studied for initializing turbulence at the inflow, including 1) imposing temperature and momentum perturbations, 2) the Veers method, 3) the Mann method, and 4) velocity perturbations from TurbSim superimposed on WRF-derived inflow. All are found to be effective at generating turbulence at the microscale and comparisons will be shown.
The team continued to develop, test, and evaluate techniques to couple the mesoscale to the microscale. A basic technique is nesting from WRF run in mesoscale mode into the WRF-LES mode. The team also studied offline coupling between WRF-mesoscale model simulations and stand-alone LES models. Two methods to integrate the mesoscale influence into the microscale solver include 1) applying the large-scale advective and pressure-gradient terms extracted from the mesoscale simulation to the governing equations of the microscale solver, and 2) assimilating the mesoscale time-height history of mean wind velocity and potential temperature to generate microscale source terms.
The MMC team has determined strategies to work through the remaining issues required to optimally provide coupled model simulations. These simulations are expected to provide the wind industry new tools that can be used in the planning, design, layout, and optimization of wind plants, thus facilitating deploying higher capacities of wind generation.