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.



College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering



Date Submitted


Document Type





vertical-axis wind turbine, wind farm optimization, wake model, turbine acoustics, computational fluid dynamics