Browsing by Subject "Wind Turbines"

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    Controlling A Meandering Wake
    (2019-12) Singh, Parul
    In this thesis we present a technique to design measurement feedback H_2 controllers for high-order nonlinear systems. The approach presented in this thesis allows insights into choosing potential measurement locations for designing measurement feedback controllers for the high-order nonlinear systems. This approach is fairly general and only requires that snapshots of system state, inputs and outputs can be collected. In this thesis, the proposed control design technique is validated on a simplified wind farm model to reduce wake meandering behind wind turbines. The control design and analysis proceeds in multiple steps. First, a linear reduced order model of the turbine is obtained using snapshots from a higher-order nonlinear 2D actuator disk model. A static full-information feedback H_2 controller is synthesized for the reduced order linear model by solving a set of linear matrix inequalities. The full-information controller has access to all the reduced-order model states as well as disturbance. The state feedback gains from full-information feedback control design are lifted to approximate the state feedback gains for the full-order system states. The magnitude of these lifted gains provides information about the full-order states most important to the controller. The measurement points for a measurement-feedback design are then determined using these state locations. Another reduced-order model is obtained for measurement feedback design and a dynamic measurement feedback H_2 controller is designed for it. The control performance is evaluated by simulations on the higher order nonlinear model. The approach to design a measurement feedback controller is also extended to parameter varying models using gain-scheduling.
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    Methods to Improve the Efficiency of Hydrostatic Transmissions in Wind Turbines
    (2022-12) Escobar Naranjo, Daniel
    Our research group has previously proposed using Hydrostatic Transmissions (HST) for wind turbines. The results have been encouraging, but the system's efficiency has always been a concern compared to a conventional gearbox. This work aims to approach the problem through three different formulations, including blade pitch oscillations, HST wind turbine control using Extremum Seeking Control (ESC), and dynamic temperature control to optimize the efficiency of the HST. The first approach involves oscillating the blades of the turbine to increase the lift coefficient and, in turn, improve power capture. A series of CFD simulations and optimizations were performed on a simplified blade model to evaluate if this is beneficial for power capture in horizontal-axis wind turbines. The results show that the optimal conditions are the same as the static blade conditions. These results happen because the drag coefficient rises exponentially as the lift coefficient rises. Also, there is a power loss due to the power required to oscillate the three blades. The second approach involves using extremum seeking control (ESC) to continuously adapt the torque gain in a modified kω^2 control law. The k gain is a constant value that highly depends on wind turbine parameters, the C_p vs. λ curve, and uncertain wind conditions. The turbine will not operate under optimal conditions if these parameters change over time. Adapting k by using ESC allows for optimal operation under any conditions. For the conditions considered, simulations and experiments showed that ESC improves power capture by 2.8% to 12.3%. The third approach involves controlling the temperature of the hydraulic oil to optimize the viscosity, which improves efficiency. A simplified model based on the friction and leakage losses of a hydraulic pump and a hydraulic motor is used to find the optimum operating point. Two control strategies are evaluated through simulations, classic proportional plus integral control (PI) and Sliding Mode Control (SMC). SMC is chosen due to its quick and robust response and low computational needs. Experimental validations showed that this approach leads to a 0.8% to 0.9% efficiency improvement compared to constant temperature control, although the improvement depends on operating conditions. Overall, these three approaches show potential for improving the efficiency of HSTs in wind turbines, with the second and third approaches showing the most promise. However, further research and experimentation will be needed to fully understand and optimize the use of HSTs in wind turbines.