4.2.2. Fatigue Loads

The effect on the fatigue loads can be seen in Figure 10. The only significant differences occur for *M*TB *<sup>X</sup>* and *<sup>M</sup>*TB *<sup>Y</sup>* , with TUBCon simulations showing a 3% and 2% increase respectively, compared to simulations with the DTU controller. The differences in *M*TB *<sup>Y</sup>* come from the larger oscillations of Ω in the TUBCon simulations, driven by the more aggressive constant power controller. The increased fatigue loads of *M*TB *<sup>X</sup>* are only indirectly affected by controller action and it is therefore more difficult to find the source of this difference. It is assumed that the different variations of Ω lead to differences in the induced tower

oscillations. For the fore-aft direction, the tower vibrations are damped out quickly due to aerodynamic damping. This is not the case in the side-side direction as the damping is much lower and hence these vibrations cause different amounts of *M*TB *<sup>X</sup>* fatigue loads. Further investigation is needed to corroborate this assumption.

**Figure 10.** Normalized lifetime Damage Equivalent Loads (DELs) for considered sensors. Nomenclature is found in Table 5.

All in all the differences in controller behavior and turbine loading remain small and the performance of both controllers is very similar.

## **5. Fatigue Load Reduction through Advanced Control Action**

As discussed in [27], many implementations of the BEM aerodynamic model average the axial induction factor across the turbine rotor. This leads to inaccuracies in the local induced velocities on the blades and hence to significant loading differences when compared to the more accurate LLFVW aerodynamic method.

These differences will necessarily affect the performance of advanced control strategies such as IPC. Firstly, the input signals of the IPC controller will be different in LLFVW simulations because of the more accurate estimation of *M*BR *<sup>Y</sup>* in each blade compared to BEM-based simulations. Secondly, the controller action will affect the turbine loads differently due to the more accurate representation of the non-homogeneous induction field in LLFVW simulations caused by the individual pitch positions.

In this section we explore the load reduction potential of the IPC control strategy (Section 3.2.2) using the LLFVW method from QBlade. This will give us a more accurate picture of the load reduction capabilities of this strategy. The IPC strategy focuses on reducing the once-per-revolution (1P) *M*BR *<sup>Y</sup>* loads. The parameters were taken from the report [9] and slightly adapted to account for the different coordinate system in which the input is measured. Since we are interested mainly in fatigue load reduction, we considered the same load cases from Table 4 (column "Turbulent calculations"). These load cases correspond to the DLC group 1.2 from [21]. For onshore wind turbines, the DLC group 1.2 is the main contributor of lifetime fatigue loads for most of the turbine components, since the turbine spends most of its operating time in these conditions [41]. Evaluating the fatigue loads from this group will therefore give a close estimate of the real fatigue loads. To keep consistency, we considered the same load sensors and metrics as the ones described in Section 4.2.
