# Model Based Open-Loop Wind Farm Control Using Active Power for Power Increase and Load Reduction
## 4 Discussion
### Comparison of Other Models  
Table 2 shows the experimental and simulation results of wind farm control available in the literature for comparison. A few experimental results are available in the literature. Based on the table, the results from the experiment showed 4.5-5% increase in power with the manual blade pitching of 2\({}^{\circ}\). However, more experimental validation seems necessary for a concrete conclusion. The simulation results using the Jensen linear wake model showed relatively high power increase. They were 10.57% increase with an optimal control and 6.24% increase with a manual adjustment of the tip speed ratio (TSR). The simulation results with more advanced wake models based on Parabolic Reynolds averaged Navier-Stokes equation (RANS) such as [PERSON]'s eddy viscosity model or UPMWAKE showed the power increase from 2.85% to 4.5% depending on the turbine spacing and the control type. The power increases were slightly lower than those from the [PERSON] wake model because the Jensen model with the wake decay constant of 0.04 (recommend for offshore application) is known to be equivalent to the ambient turbulence intensity of approximately 8-10%. Therefore, the wake recovery with the Jensen model is expected to be faster than the wake recovery in the location where the turbulence intensity is lower than. The results from the LES simulation with an actuator disk or an actuator line method showed some discrepancy. The manual blade pitching with the LES simulation showed the power decreases of \(-2.2\%\) and \(-8.9\%\) with the blade pitching angle of 2\({}^{\circ}\). The largest decrease in the power  
Figure 12: Simulation Results for Tower Load Variation: (**a–c**) DEL variation of the first wind turbine according to turbulence intensity and control type(@wind farm control frequency: 0.01, 0.05, 0.1 Hz); (**d–f**) DEL variation of the second wind turbine according to turbulence intensity and control type(@wind farm control frequency: 0.01, 0.05, 0.1 Hz) (**g–i**) DEL variation of the third wind turbine according to turbulence intensity and control type(@wind farm control frequency: 0.01, 0.05, 0.1 Hz).  
was obtained with five wind turbines in series and, with the blade pitching of the most upstream wind turbine, the power outputs from the four upstream wind turbine were all decreased and the power of the fifth wind turbine was slightly increased compared with the reference baseline control. The reason for this unusual result is explained to be due to the wake meandering effect by the authors of the literature. Unlike the two results with the LES simulation, the optimal control algorithm applied to the LES simulation with an actuator disk model showed the power increase of 16%. However, the wind turbine control algorithms and wind turbine dynamics were not used in the study and this might reduce the power increase. Although the results in Table 2 were obtained with different conditions and cannot be compared directly, the results in this study with the proposed model predictive open loop wind farm control are within the range of the results obtained from other studies, and the power gains are relatively low. The reason for this is considered to be that more realistic conditions including wind turbine dynamics, wind turbine control, and wind farm control frequency have been added in the simulation of this study. However, experimental study must be done as a future work to fully validate the result.