Nonlinear Optimal Control Of Wind Turbines To Extract Maximum Power Using Hybrid Homotopy Method

نوع: Type: thesis

مقطع: Segment: PHD

عنوان: Title: Nonlinear Optimal Control Of Wind Turbines To Extract Maximum Power Using Hybrid Homotopy Method

ارائه دهنده: Provider: Arefe Shalbafian

اساتید راهنما: Supervisors: Dr. Soheil Ganjefar

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr. Mohammad Hasan Moradi, Dr. Kamal hosseini sani, Dr. Hadi delavari

زمان و تاریخ ارائه: Time and date of presentation: 7December 2022-3 pm

مکان ارائه: Place of presentation: Seminar2

چکیده: Abstract: Since wind turbines have inherent nonlinear properties, the linear controllers cannot ensure high efficiency. Thus, it is necessary to consider the nonlinear dynamic model of wind turbines to achieve the desired performance. In this thesis, a robust nonlinear optimal controller has been designed for the wind turbine to capture maximum wind power from the wind and attenuate the mechanical stress on the drive train. The proposed strategy is based on the combination of the nonlinear optimal control method and sliding mode control approach. In the first strategy, we design the nonlinear optimal controller for the wind turbine. In the next step, we design the hybrid robust optimal controller to make the system robust against disturbances. In general, a nonlinear optimal controller for nonlinear systems can be designed by solving the partial differential equation called the Hamilton–Jacobi–Bellman (HJB) equation. This equation is a partial differential equation and it is difficult to calculate its analytic solution. First, the HJB equation corresponding to the one-mass and two-mass models of the wind turbine is extracted. Next, the homotopy perturbation method (HPM) is applied to solve the HJB equation corresponding to variable-speed fixed-pitch wind turbines. In the next step, a new strategy called the optimal homotopy asymptotic method (OHAM) is proposed to solve the HJB equation (in the general case). Thus, this method, which has higher accuracy and speed than the HPM, is employed to achieve the approximate solution of the HJB equation related to the variable speed wind turbine. The OHAM approach only requires a few iterations to achieve an accurate solution. In comparison to HPM, the OHAM algorithm is faster and requires fewer iterations. As a result, computational costs are reduced and implementation becomes easy. In other words, a good compromise between simplicity and efficiency is achieved by applying the OHAM controller. The OHAM controller is able to capture the maximum wind energy, reduce the mechanical stresses on the drive-train, and achieve fast convergence in finite-time by applying a small control input. Another issue is the robustness of the system against uncertainties and disturbances. Although the optimal controller results in reduced control input, this controller is very sensitive to uncertainties. Thus, the inability of the optimal controller to provide sufficient robustness against uncertainties and various disturbances in the system is a challenging issue. This problem can be solved by integrating the optimal controller with a robust controller. In the next strategy, we integrate the robust sliding mode controller with the optimal controller to achieve the required robustness. Fast convergence in finite time is one of the main challenges for sliding mode control. A large input can be applied to achieve faster convergence, but this can have adverse effects on the system and is undesirable in practical implementation. Since the optimal controller can reduce the control input, merging the optimal controller with sliding mode control is an effective way to deal with this problem. In other words, the proposed hybrid controller has both robustness against uncertainties and optimal control performance. Thus, the proposed control scheme requires a small control input and is robust against uncertainties. Traditional sliding mode control suffers from an undesirable drawback known as the chattering problem. Thus, we integrate the nonlinear optimal controller with a second-order sliding mode controller to attenuate the chattering phenomenon. The hybrid designed controller is able to maximize the wind power capture, minimize the control input, attenuate the mechanical stress on the drive-train, achieve fast convergence, modify the transient response, deal with the chattering problem, and ensure safe operation for wind turbine systems in the presence of uncertainties.

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