Growing concerns about the environmental impact of fossil fuel energy and
improvements in both the cost and performance of wind turbine technologies has spurred
a sharp expansion in wind energy generation. However, both the increasing size of wind
farms and the increased contribution of wind energy to the overall electricity generation
market has created new challenges. As wind farms grow in size and power density, the
aerodynamic wake interactions that occur between neighboring turbines become
increasingly important in characterizing the unsteady turbine loads and power output of
the farm. Turbine wake interactions also impact variability of farm power generation,
acting either to increase variability or decrease variability depending on the wind farm
control algorithm. In this dissertation, both the unsteady vortex wake loading and the
effect of wake interaction on farm power variability are investigated in order to better
understand the fundamental physics that govern these processes and to better control
wind farm operations to mitigate negative effects of wake interaction.
The first part of the dissertation examines the effect of wake interactions between
neighboring turbines on the variability in power output of a wind farm, demonstrating
that turbine wake interactions can have a beneficial effect on reducing wind farm
variability if the farm is properly controlled. In order to balance multiple objectives, such
as maximizing farm power generation while reducing power variability, a model
predictive control (MPC) technique with a novel farm power variability minimization
objective function is utilized. The controller operation is influenced by a number of
different time scales, including the MPC time horizon, the delay time between turbines,
and the fluctuation time scales inherent in the incident wind. In the current research, a
non-linear MPC technique is developed and used to investigate the effect of three time
scales on wind farm operation and on variability in farm power output. The goal of the
proposed controller is to explore the behavior of an ideal farm-level MPC controller
with different wind, delay and horizon time scales and to examine the reduction of
system power variability that is possible in such a controller by effective use of wake
interactions.
The second part of the dissertation addresses the unsteady vortex loading on a
downstream turbine caused by the interaction of the turbine blades with coherent vortex
structures found within the upstream turbine wake. Periodic, stochastic, and transient
loads all have an impact on the lifetime of the wind turbine blades and drivetrain. Vortex
cutting (or vortex chopping) is a type of stochastic load that is commonly observed when
a propeller or blade passes through a vortex structure and the blade width is of the same
order of magnitude as the vortex core diameter. A series of Navier-Stokes simulations of
vortex cutting with and without axial flow are presented. The goal of this research is to
better understand the challenging physics of vortex cutting by the blade rotor, as well as
to develop a simple, physics-based, validated expression to characterize the unsteady
force induced by vorte
