Abstract
A mid-fidelity simulation framework for large offshore wind farms has been developed at
SINTEF, for the efficient joint modelling of active power control and structural degradation
due to fatigue damage. It bridges two fields of research that are traditionally split: grid
integration and mitigation of asset degradation, through multi-objective wind farm
control. Component-level damage is brought to farm-level simulations. There, damage
and power demand from the grid are linked to stochastic loads and power fluctuations
arising from turbulence in the wind, on which a particular emphasis has been set. In a joint
project with NTNU, this has been applied to the mitigation of the degradation of power
train components (gears and bearings) in curtailed (down-regulated) wind conditions. It is
shown that when a farm is requested not to operate at its full available power by the grid
operator, it is possible to —to some extent— steer degradation to better fit maintenance
scheduling or lifetime extension plans to further reduce LCOE.
The framework has been developed in parallel projects in synergy with NorthWind and
consists of four main features: (1) a wind farm simulator adapted for stochastic
simulations of large wind farms in down-regulated operation, (2) a farm-wide turbulence
generator, (3) a wind farm controller and (4) a database for drivetrain degradation based
on turbine- and component-level simulations. This report first introduces the concept and
motivation, then presents each of the above-mentioned features before linking them in a
case study.
SINTEF, for the efficient joint modelling of active power control and structural degradation
due to fatigue damage. It bridges two fields of research that are traditionally split: grid
integration and mitigation of asset degradation, through multi-objective wind farm
control. Component-level damage is brought to farm-level simulations. There, damage
and power demand from the grid are linked to stochastic loads and power fluctuations
arising from turbulence in the wind, on which a particular emphasis has been set. In a joint
project with NTNU, this has been applied to the mitigation of the degradation of power
train components (gears and bearings) in curtailed (down-regulated) wind conditions. It is
shown that when a farm is requested not to operate at its full available power by the grid
operator, it is possible to —to some extent— steer degradation to better fit maintenance
scheduling or lifetime extension plans to further reduce LCOE.
The framework has been developed in parallel projects in synergy with NorthWind and
consists of four main features: (1) a wind farm simulator adapted for stochastic
simulations of large wind farms in down-regulated operation, (2) a farm-wide turbulence
generator, (3) a wind farm controller and (4) a database for drivetrain degradation based
on turbine- and component-level simulations. This report first introduces the concept and
motivation, then presents each of the above-mentioned features before linking them in a
case study.
