直驱式永磁同步风力发电系统控制研究

发布时间：2019-04-01 10:20

【摘要】：随着社会的不断发展和人口的不断增加,能源与环境问题日益严重。为了社会的可持续发展,人类正在致力于新能源的开发和利用。作为发展最快、开发最具规模的可再生能源,风能扮演着尤为重要的角色。在众多风力发电系统中,直驱式永磁同步风力发电系统由于其结构简单、效率高、可靠性高等特点,正受到越来越多的关注,对直驱式永磁同步风力发电系统控制的研究也成为了热点。论文首先分析了风力机的运行特性,在额定风速以下运行在发电机控制模式,采用最大功率跟踪算法实现风力机的最大风能捕获,在额定风速以上采用变桨距控制模式,限制风力机捕获的风能；然后,建立了永磁同步电机和双PWM变流器的数学模型,机侧变流器采用id=0的电流矢量定向控制策略,网侧变流器采用电压矢量定向控制策略。最后,在MATLAB中建立了直驱式永磁同步风力发电系统的仿真模型,为之后的变桨距控制和低电压穿越控制研究打下基础。在构建了直驱式永磁同步风力发电系统的模型之后,重点对直驱式永磁同步风力发电系统的变桨距控制进行了研究,将适合于非线性系统控制的模糊神经网络算法引入到风力机变桨距控制中,设计了一种基于功率变化的模糊神经网络变桨距控制器。仿真结果表明：该模糊神经网络变桨距控制器能够记忆专家的控制经验,可以更好的适应风电系统随机性强、不确定因素多的特点,具有较强鲁棒性和抗干扰能力,其控制效果优于传统的PD变桨距控制器。在低电压穿越控制方面,首先分析了直驱式永磁同步风力发电系统在电网发生低电压故障时功率传输的暂态过程；然后研究了基于耗能和储能的两种Crowbar低电压保护方案,并对其进行了MATLAB仿真,比较了两种保护方案的优缺点；研究了电网低电压故障时的无功补偿策略及两种低电压穿越辅助控制策略。最后,结合现有的低电压穿越控制策略提出了一种低电压穿越综合控制逻辑,并对其低电压穿越效果进行了MATLAB仿真验证,仿真结果表明了其可行性。
[Abstract]:With the development of society and the increase of population, energy and environment problems are becoming more and more serious. For the sustainable development of society, mankind is committed to the development and utilization of new energy. Wind energy plays a particularly important role as the fastest developing and the most large-scale renewable energy. In many wind power generation systems, the direct drive permanent magnet synchronous wind power system has attracted more and more attention due to its simple structure, high efficiency and high reliability. The control of direct drive permanent magnet synchronous wind power generation system has also become a hot spot. Firstly, the paper analyzes the operating characteristics of wind turbine, runs under rated wind speed in generator control mode, adopts maximum power tracking algorithm to realize maximum wind energy capture of wind turbine, and adopts variable pitch control mode above rated wind speed. Limiting wind energy captured by wind turbines; Then, the mathematical models of permanent magnet synchronous motor (PMSM) and dual PWM converter are established. The current vector oriented control strategy of id=0 is adopted in the machine side converter and the voltage vector directional control strategy is used in the grid side converter. Finally, the simulation model of direct drive permanent magnet synchronous wind power generation system is established in MATLAB, which lays a foundation for further research on pitch control and low voltage traversal control. After the model of direct drive permanent magnet synchronous wind power generation system is constructed, the pitch control of direct drive permanent magnet synchronous wind power generation system is studied. The fuzzy neural network algorithm suitable for nonlinear system control is introduced into variable pitch control of wind turbine. A fuzzy neural network pitch controller based on power variation is designed. The simulation results show that the fuzzy neural network variable pitch controller can memorize the control experience of experts, and can better adapt to the characteristics of strong randomness, many uncertain factors and strong robustness and anti-jamming ability of wind power system. The control effect is better than the traditional PD pitch controller. In the aspect of low voltage traversal control, the transient process of power transmission in direct drive permanent magnet synchronous wind power generation system is analyzed when the low voltage fault occurs in the power grid. Secondly, two Crowbar low voltage protection schemes based on energy consumption and energy storage are studied and simulated by MATLAB, and the advantages and disadvantages of the two protection schemes are compared. The reactive power compensation strategy and two auxiliary control strategies for low voltage traversing in power network are studied in this paper. Finally, combined with the existing low-voltage traversal control strategy, a low-voltage traversing comprehensive control logic is proposed, and its low-voltage traversal effect is verified by MATLAB simulation. The simulation results show that the low-voltage traversal control logic is feasible.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614

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