Wind Energy Conversion System Analysis,Control And Optimization Methods

Wind is a renewable green energy source, which has a broad prospect of application. The wind energy conversion system(WECS)consists of aerodynamics subsystem, electromagnetic subsystem and the grid connection subsystem. Taking into account the complexity and particularity of the wind energy conversion system, its controller should be able to satisfy difficult control goals. So it is the key issue to do some research on the optimal control strategies of the WECS. Based on the modeling of the system, by introducing the advanced nonlinear optimal control theory, it is of great theory and engineering value for the prospect of the WECS to research the optimal control using mixed criteria with great precision, high efficiency and excellent performance.The wind turbine, transmission system, generator and the servo system are modeled separately. According to the multi-time scale characteristic of wind speed, the wind speed is divided into low-frequency component and high-frequency turbulent component. Then a two-frequency model is established for wind energy conversion system, which lays the foundation for the research of optimal control algorithm.Wind energy is a random, filminic, unstable energy, which makes the wind conversion system full of uncertainties. Therefore, a fuzzy adaptive control method is proposed to maximize the wind energy capture ratio. Firstly, the model reference fuzzy adaptive control (MRFAC) uses the inputs and outputs during the process of wind transformation to adjust the parameters online, then the system's dynamic performance is improved. Secondly, the fuzzy controller is embedded into the model reference adaptive control system, acting as the adaptive inverse model to instead of conventional adaptive algorithm. The proposed method is easy to implement, furthermore, it has strong robustness and can improve the system's dynamic performance.Considering the uncertainties of the paramaters and the unknown interferences of a WECS, a H∞mixed sensitivity robust control method which is used to control the rotational speed of the generator is introduced. Using this method, the robust weighted function is choosen according the system charicteristics to achieve the goal of maximizing the wind capture ratio below the rated wind speed as well as great robustness. Further, the LPV theory is introduced after the high-frequency LPV model of the WECS is established, a H∞controller is proposed which can dynamically compensate the paramaters.For the multi-objective needs such as the maximizing the wind capture ratio and minimizing the torque perturbation, a two-frequency loop structure is designed based on the two-frequency loop model of the WECS. PI control is used in the low-frequency loop, while different control methods are given in the high-frequency-loop. First of all, H∞is adopted, by choosing the right weighted function, the controller can be obtained by solving the linear matrix inequalities (LMI). Secondly, H2/H-infinity is used to overcome the random measurement noises and disturbances.The mimimal H2 performance index is solved by adjusting the H-infinity index. Applying this controller into the systm, both of the objectives are satisfied very well. Finally, by introducing the LPV model, a variable gain-scheduling controller based on the H-infinity state feedback is designed to compensate the low frequency controller.To validate the feasibility of the works of this thesis, a wind generator control system hardware testing platform is constructed based on dSPACE in Lab. Digital signal processor (DSP) is employed as the core of the turbine simulator.The system is tested in the way of RCP.The experimental results show that the proposed methods can meet the multi-objective requirements of the WECS satisfactively.