Wake interactions on a floating platform for offshore wind energy applications were investigated. The study is performed in collaboration with Hexicon AB which has a patent family for innovative floating platforms, which are able to turn automatically. The Jensen model is used for wake effect calculations and the simulations were performed in MATLAB. The present study starts with wind speed and wind direction data analysis for the specific site that Hexicon AB plans to construct its first platform. Data analysis is followed by wake interaction studies for H4-24MW type Hexicon AB platform. Wake interaction simulations were performed for three different cases. Fixed turbine and platform, Nacelle yawing and fixed platform and Nacelle yawing and turned platform. Different cases were investigated in order to see wake interactions for different wind directions. Wind direction effect on wake interactions were performed between _90_ and 90_ with an increment of 10_. After having the simulation results for Nacelle yawing and turned platform case the results were compared with ANSYS - CFX simulations results. The results didn’t match exactly but they were very close, which is an indicator to the validity of the Jensen Model. After finding out the possible behavior of wake interactions for different wind directions, power calculations were performed for the same three cases. In order to perform the power calculations the wake interactions for different wind directions were taken into account. In case of platform turning it was assumed that power losses were caused both by wake interactions and in case of thrusters activation. The losses that would be caused by different thrust forces on the turbine blades were not included. The last study was performed to suggest different layouts. In the second case, Nacelle yawing and fixed platform, it was found out that nacelle yawing for most of the angles is not possible because it creates wake regions in front of the rotor area. It was decided to propose new turbine configurations on the platform which are tolerant to different nacelle yawing angles. The simulations were run without considering any constructions limitations, meaning that the availability of platform structure was not included. The study is ended by performing some probabilistic results for platform turning behavior.

Wake interactions on a floating platform for offshore wind energy applications were investigated.The study is performed in collaboration with Hexicon AB which has a patent family for innovative floating platforms, which are able to turn automatically. The Jensen model is used for wake effect calculations and the simulations were performed in MATLAB. The present study starts with wind speed and wind direction data analysis for the specific site that Hexicon AB plans to construct its first platform. Data analysis is followed by wake interaction studies for H4-24MW type Hexicon AB platform. Wake interaction simulations were performed for three different cases. Fixed turbine and platform, Nacelle yawing and fixed platform and Nacelle yawing and turned platform. Different cases were investigated in order to see wake interactions for different wind directions. Wind direction effect on wake interactions were performed between _90_ and 90_ with an increment of 10_. After having the simulation results for Nacelle yawing and turned platform case the results were compared with ANSYS - CFX simulations results. The results didn’t match exactly but they were very close, which is an indicator to the validity of the Jensen Model. After finding out the possible behavior of wake interactions for different wind directions, power calculations were performed for the same three cases. In order to perform the power calculations the wake interactions for different wind directions were taken into account. In case of platform turning it was assumed that power losses were caused both by wake interactions and in case of thrusters activation. The losses that would be caused by different thrust forces on the turbine blades were not included. The last study was performed to suggest different layouts. In the second case, Nacelle yawing and fixed platform, it was found out that nacelle yawing for most of the angles is not possible because it creates wake regions in front of the rotor area. It was decided to propose new turbine configurations on the platform which are tolerant to different nacelle yawing angles. The simulations were run without considering any constructions limitations, meaning that the availability of platform structure was not included. The study is ended by performing some probabilistic results for platform turning behavior.

In this thesis, the effect of pitch based optimisation was explored for a 80 turbine wind farm. Using a modified Jensen wake model and the Particle Swarm Optimisation (PSO) model, a pitch optimisation strategy was created for the dominant turbulence and atmospheric condition for the wind farm. As the wake model was based on the FLORIS model developed by P.M.O Gebraad et. al., the wake and power model was compared with the FLORIS model and a -0.090% difference was found. To determine the dynamic predictive capability of the wake model, measurement values across a 10 minute period for a 19 wind turbine array were used and the wake model under predicted the power production by 17.55%. Despite its poor dynamic predictive capability, the wake model was shown to accurately match the AEP production of the wind farm when compared to a CFD simulation done in FarmFlow and only gave a 3.10% over-prediction. When the optimisation model was applied with 150 iterations and particles, the AEP production of the wind farm increased by 0.1052%, proving that the pitch optimisation method works for the examined wind farm. When the iterations and particles used for the optimisation was increased to 250, the power improvement between optimised results improved by 0.1144% at a 222.5% increase in computational time, suggesting that the solution has yet to fully converge. While the solutions did not fully converge, they converged sufficiently and an increase in iterations gave diminishing results. From the results, the pitch optimisation model was found to give a significant increase in power production, especially in wake intensive wind directions. However, the dynamic predictive capabilities will have be improved upon before the control strategy can be applied to an operational wind farm.

In this thesis, the effect of pitch based optimisation was explored for a 80 turbine wind farm. Using a modified Jensen wake model and the Particle Swarm Optimisation (PSO) model, a pitch optimisation strategy was created for the dominant turbulence and atmospheric condition for the wind farm. As the wake model was based on the FLORIS model developed by P.M.O Gebraad et. al., the wake and power model was compared with the FLORIS model and a -0.090% difference was found. To determine the dynamic predictive capability of the wake model, measurement values across a 10 minute period for a 19 wind turbine array were used and the wake model under predicted the power production by 17.55%. Despite its poor dynamic predictive capability, the wake model was shown to accurately match the AEP production of the wind farm when compared to a CFD simulation done in FarmFlow and only gave a 3.10% over-prediction. When the optimisation model was applied with 150 iterations and particles, the AEP production of the wind farm increased by 0.1052%, proving that the pitch optimisation method works for the examined wind farm. When the iterations and particles used for the optimisation was increased to 250, the power improvement between optimised results improved by 0.1144% at a 222.5% increase in computational time, suggesting that the solution has yet to fully converge. While the solutions did not fully converge, they converged sufficiently and an increase in iterations gave diminishing results. From the results, the pitch optimisation model was found to give a significant increase in power production, especially in wake intensive wind directions. However, the dynamic predictive capabilities will have be improved upon before the control strategy can be applied to an operational wind farm.