Abstract:
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Background: Wind energy is one of the leading renewable energies that take part in the current
transition from the usage of traditional fossil-fuel energies to green ones. The potential
and development of wind power is increasing constantly. Therefore, continuous studies are being
carried out in order to improve the power extraction of wind farms.
Study: This Master’s Thesis aims to obtain multiple-Input-multiple-Output Reduced-Order
Models (IOROMs) that are able to capture the main dynamics present in wind turbine wake
flows within wind farms during transients and during operation. This dynamics can be excited
via different inputs, such as wind turbine’s yaw angle, generator torque, pitch angle, among
others. In this work, the study will be conducted by analyzing the response of the system to yaw
angle variations, although the same procedure explained is valid for other inputs. The models
developed are also mainly intended for capturing the relation between output magnitudes, such
as wind turbine power output, bending moments, lateral forces, etc., and the given inputs to
the system. Beside, order reduction is key to this work, since the models are expected to reproduce
with acceptable fidelity high computationally costly simulations. The study has been
conducted based on CFD (Computational Fluid Dynamics) simulation data that are considered
as the starting point of the work.
Results & Conclusions: The models developed in this work present considerable agreement
with respect to the results obtained via CFD simulations. Owing to the symmetry that the
yawing motion presents for the system, the operational range has been divided into two sides,
namely the positive yaw angles side and the negative yaw angles side. The results for both
cases are successful in terms of flow and power output reconstruction. Therefore, the models can
predict within seconds the behavior of wind farms whose performance takes days to be known
through CFD simulations. This work also presents several improvements as future upgrade
for reduced-order models obtained from CFD data. Some of these improvements deal with
operational ranges, sample time, and data collection, inter alia. |