Mean Kinetic Energy Fluxes within Wind Farms through a Diurnal Cycle

Wind energy has stood as a prominent element of the mix of renewable energies, with a remarkable growth of 23% over the past decade [1]. For wind energy to be profitable, large arrays of wind turbines have been placed in optimal locations, configuring large wind farms. However, the capacity for the atmospheric turbulent flow to immediately recover after circulation through a succession of wind turbines is limited and the momentum deficit within the atmospheric flow is recovered differently depending on the background atmospheric stratification and packing of the wind farm. To improve our current understanding of the flow capacity to recover downstream of wind turbines, this research project presents a set of Large Eddy Simulations trough a diurnal cycle and using different wind farm packing arrangements. These simulations are forced with a constant geostrophic wind and a time varying surface temperature, extracted from a selected period of the CASES-99 field experiment, and wind turbines are represented with the actuator disk model with rotation and yaw alignment. A control volume analysis for each wind turbine composing the wind farm has been used to evaluate the mean kinetic energy fluxes per unit surface. This analysis shows the existence of two dominant mechanisms for wind turbine wake recovery: advection and vertical flux ok mean kinetic energy. For the low-packing arrangements advection dominates, while as packing increases the mean kinetic energy recovery is progressively result of the vertical fluxes. As one could initially expect the power harvested by the wind turbines is in direct synchronization with both wake recovery methods. Results will illustrate these findings as well as a relationship linking the evolution of harvested power as a function of wind farm packing and background atmospheric stratification.

[1] GWEC, Wind energy technology, Tech. Rep. (2014).