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This thesis focuses on providing the means to use vertical-axis wind turbines (VAWTs) in wind farms as an alternative form of harnessing wind energy in offshore and urban environments where both wake and acoustic effects of turbines are important considerations. In order for VAWTs to be used in wind farm layout analysis and optimization, a reduced-order wake model is needed to calculate velocities around a turbine quickly and accurately. However, a VAWT wake model has not been available to accomplish this task. Using vorticity data from computational fluid dynamic (CFD) simulations of VAWTs and cross-validated Gaussian distribution and polynomial surface fitting, a wake model is produced that can estimate a wake velocity deficit of an isolated VAWT at any downstream and lateral position based on nondimensional parameters describing the turbine speed and geometry. When compared to CFD, which takes over a day to run one simulation, the wake model predicts the velocity deficit at any location with a normalized root mean squared error of 0.059 in about 0.02 seconds. The model agrees with two experimental VAWT wake studies with a percent difference of the maximum wake deficit of 6.3% and 14.6%. Using the actuator cylinder model with predicted wake velocities of multiple turbines, aerodynamic loads can be calculated on the turbine blades to estimate the power production of a VAWT wind farm. As VAWTs could be used in urban environments near residential areas, the noise disturbance coming from the turbine blades is an important consideration in the layout of a wind farm. Noise restrictions may be imposed on a wind farm to limit the disturbance, often impacting the wind farm's power producing capability. Two specific horizontal-axis wind turbine farm designs are studied and optimized using the FLORIS wake model and an acoustic model based on semi-empirical turbine noise calculations to demonstrate the impact a noise level constraint has on maximizing wind farm power production. When a noise level constraint was not active, the average power production increased, up to 8.01% in one wind farm and 3.63% in the other. Including a noise restriction in the optimization had about a 5% impact on the optimal average power production over a 5 decibel range. By analyzing power and noise together, the multi-modality of the optimization problem can be used to find solutions were noise impact can be improved while still maximizing wind farm power production.

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.

[pt] À medida que o mundo enfrenta a urgente questão das mudanças climáticas, a energia eólica se destaca como uma fonte crítica de energia limpa. No entanto, realizar seu pleno potencial depende da otimização dos layouts de parques eólicos, especialmente à luz do complexo efeito de esteira. Esta dissertação adentra na Otimização de Layout de Parques Eólicos (WFLO, na sigla em inglês) usando o Modelo de Efeito de Esteira de Bastankhah. O escopo deste estudo vai além do design de layout; abrange a intrincada tarefa de mitigar o impacto do efeito de esteira, juntamente com a busca por uma estratégia de negociação com aversão ao risco e maximização de valor. Para contabilizar a aversão ao risco, uma combinação entre o Valor Esperado e os funcionais de medida de risco baseados no quantil esquerdo, a medida de Valor em Risco Condicional (CVaR). Para apoiar esta pesquisa, um pacote de código aberto OptimalLayout.jl foi desenvolvido. Este pacote co-otimiza o posicionamento das turbinas eólicas para mitigar o impacto do efeito de esteira e a estratégia de contratação de um agente/gerador avesso ao risco. Através de uma série de estudos de casos práticos em diversos ambientes dinâmicos, esta pesquisa ilustra a aplicabilidade do WFLO no mundo real. Estas investigações examinam detalhadamente a sua influência na produção de energia e na dinâmica das receitas, oferecendo informações valiosas sobre soluções energéticas sustentáveis. / [en] As the world confronts the pressing issue of climate change, wind power stands out as a critical source of clean energy. However, realizing its full potential relies on the optimization of wind farm layouts, particularly in light of the complex wake effect. This dissertation delves into Wind Farm Layout Optimization (WFLO) using the Bastankhah Wake Model. The scope of this study goes beyond layout design; it encompasses the intricate task of mitigating the wake effect s impact along with the seek for a risk-averse-value maximizing trading strategy. To account for risk-averseness, a combination between Expected Value and the left-side-quantile-based risk-measure functionals, the Conditional Value-at-Risk (CVaR) measure. To support this research, an opensource package OptimalLayout.jl was developed. This package co-optimizes the positioning of wind turbines to mitigate wake effect impact,and the contracting strategy of a Risk-Averse agent/generator. Through a series of practical case studies across diverse dynamic environments, this research illustrates the real-world applicability of WFLO. These investigations intricately examine its influence on power production and revenue dynamics, offering valuable insights into sustainable energy solutions.

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.

Abstact: In order to address the wind-industry's need for a new generation of more advanced wake models, which accurately quantify the mean flow characteristics within a reasonably CPU-time, the two-dimensional analytical approach by Belcher et al. (2003) has been extended to a three-dimensional wake model. Hereby, the boundary-layer approximation of the Navier-Stokes equations has been linearized around an undisturbed baseflow, assuming that the wind turbines provoke a small perturbation of the velocity field. The conducted linearization of the well established actuator-disc theory brought valuable additional insights that could be used to understand the behavior (as well as the limitations) of a model based on linear methods. Hereby, one of the results was that an adjustment of the thrust coecient is necessary in order to get the same wake-velocity field within the used linear framework. In this thesis, two different datasets from experiments conducted in two different wind-tunnel facilities were used in order to validate the proposed model against wind-farm and single-turbine cases. The developed model is, in contrary to current engineering wake models, able to account for effects occurring in the upstream flow region. The measurement, as well as the simulations, show that the presence of a wind farm affects the approaching flow even far upstream of the first turbine row, which is not considered in current industrial guidelines. Despite the model assumptions, several velocity statistics above wind farms have been properly estimated, providing insight about the transfer of momentum inside the turbine rows. Overall, a promising preliminary version of a wake model is introduced, which can be extended arbitrarily depending on the regarded purpose.

A new vortex model for wind turbines was developed in order to evaluate the loads at the blades and other important characteristics of interest for the wind industry such as power and thrust coefficients. Nowadays, the calculation of these quantaties is done in a reliable and precise manner with LES simulation using actuator line or actuator disk models. However, LES simulations are computationally heavy and the model here developed aims at calculating the same quantities of interest in less time but still giving reliable and accurate results for any wind turbine model. The idea of a vortex model for wind turbines was developed by Segalini & Aöfredsson, J. Fluid Mech., vol. 725, pages 91-116, 2013, using vortex filaments to reproduce the vorticity on the blades and in the wake. Nevertheless, that model had some limitations, among which, the main one, was the impossibility to simluate wind turbines with varying circulation along the blade, something that is always present in reality. With this thesis it is proposed a model based on the one of Segalini & Alfredsson (2013) but with the introduction of a vortex sheet that allows to simulate a vorticity release from the wind turbine blades and hence wind turbines with varying circulation along the blades. The model was validated against a LES simulation of the Tjaereborg wind turbine by Sarmast, KTH Royal Institute of Technology, 2014, that utilized an actuator line model. The results confirmed the improvement of the vortex model compared to the previous one of Segalini & Alfredsson (2013) and gave consistent results regarding the flow field at the rotor plane and the loads on the blades.

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