DFIG风电场次同步振荡的分析与抑制

发布时间：2018-01-31 12:31

本文关键词： 双馈机组次同步振荡奈奎斯特稳定判据复转矩系数法附加阻尼控制器 RBF神经网络　出处：《南京理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：中国能源发展战略已将大规模开发利用风电作为其重要组成部分。由于风力资源与负荷需求分布不一致,需将风电大容量、远距离地向外输送。串联补偿电容技术具有减小输电线路损耗并同时提高线路输送容量的优点,可作为实现风电大规模外送的技术支撑,但该技术的广泛应用,同样存在可能诱发风电场次同步振荡的问题,次同步振荡的发生严重影响了大规模风电基地及外送系统的安全稳定运行。针对含双馈机组DFIG(Doubly-Fed Induction Generator)风电场经串补并网引起的次同步振荡(Sub-synchronous Oscillation,SSO)问题,本文进行了以下方面的研究:1.对DFIG风电场经串联电容并网系统进行了详细的数学建模,具体包括风能捕获的空气动力学模型、风力机轴系传动系统模型、双馈感应发电机模型、直流电容动态过程模型、转子侧变换器控制模型、网侧变换器控制模型、输线模型等。通过坐标变换实现dq解耦控制,并对转子侧变换器和网侧变换器的PI控制方式进行了详细阐述。2.用基于阻抗的奈奎斯特稳定判据对DFIG风电场次同步振荡进行初步分析,验证风速、串联补偿度对风电场次同步振荡的影响。再通过复转矩系数法进行详细分析,在发电机转子上附加小信号增量,得到电气阻尼曲线,最后使用时域仿真法直观的验证了分析结果。当风速越小、串补度越大,就越容易发生感应发电机效应(induction generator effect,IGE),引发次同步振荡。此外,转子侧变换器的电流内环的比例和积分参数越大,越容易导致由风电机组控制器引发的次同步控制相互作用(sub-synchronous control interaction,SSCI),这是风电场特有的次同步振荡形式。3.在DFIG风电场次同步振荡机理分析的基础上,采用附加阻尼控制器的方法来抑制次同步振荡。用复转矩系数法得到的电气阻尼最低点的频率和需要补偿的角度,来计算附加阻尼控制器的移相环节参数,并利用粒子群智能算法对附加阻尼控制器的参数进行寻优,附加阻尼控制器可以补偿电气阻尼,提高系统的稳定性。4.本文提出了转子侧变换器电磁转矩Te控制外环采用RBF神经网络控制取代传统PI控制的方法。在不同风速及不同串补的情况下,转矩环的RBF神经网络的自学习能力使得PID控制器具有自适应性,可适应双馈风电场不同串补以及不同风速下的复杂的运行工况。采用传统PI控制参数会诱发次同步振荡,仿真证明本文所设计的RBF神经网络控制器对次同步振荡具有良好的抑制效果。
[Abstract]:The large-scale development and utilization of wind power has been regarded as an important part of China's energy development strategy. Because the distribution of wind power resources and load demand is not consistent, large capacity of wind power is needed. The series compensation capacitor technology has the advantages of reducing the transmission line loss and increasing the transmission capacity at the same time. It can be used as the technical support to realize large-scale wind power delivery, but this technology is widely used. It is also possible to induce sub-synchronous oscillation in wind farms. The occurrence of sub-synchronous oscillation has seriously affected the safe and stable operation of large-scale wind power base and outgoing system. The subsynchronous oscillation of Doubly-Fed Induction generator wind farm caused by serialization and grid connection (. Sub-synchronous Oscillation. In this paper, the following aspects are studied: 1. The detailed mathematical model of DFIG wind farm through the series capacitance grid-connected system, including the aerodynamic model of wind energy capture, is presented in this paper. Wind turbine shafting transmission system model, doubly-fed induction generator model, DC capacitor dynamic process model, rotor side converter control model, grid-side converter control model. Through coordinate transformation, dq decoupling control is realized. The Pi control mode of the rotor side converter and the grid side converter is described in detail. 2. The subsynchronous oscillation of DFIG wind farm is preliminarily analyzed by using the Nyquist stability criterion based on impedance to verify the wind speed. The influence of series compensation degree on the sub-synchronous oscillation of wind farm is analyzed in detail by the method of complex torque coefficient, and the electrical damping curve is obtained by adding small signal increment to the generator rotor. Finally, the time domain simulation method is used to verify the analysis results intuitively. When the wind speed is smaller, the series compensation degree is larger. The more likely the induction generator effect generator effect will lead to subsynchronous oscillation. The ratio and integral parameters of the current inner loop of the rotor side converter are larger. The more easily the sub-synchronous control interaction caused by the wind turbine controller is caused by SSCI). This is the special sub-synchronous oscillation form of wind farm. 3. Based on the analysis of sub-synchronous oscillation mechanism of DFIG wind farm. The method of additional damping controller is used to suppress the sub-synchronous oscillation, and the phase shift parameters of the additional damping controller are calculated by using the frequency of the lowest point of electrical damping obtained by the method of complex torque coefficient and the angle to be compensated. Particle swarm optimization algorithm is used to optimize the parameters of the additional damping controller, which can compensate the electrical damping. In this paper, the RBF neural network control is used to replace the traditional Pi control in the outer loop of electromagnetic torque Te control of the rotor side converter. Under different wind speed and different series compensation, this paper proposes a method to improve the stability of the system. The self-learning ability of the torque loop RBF neural network makes the PID controller self-adaptive. It can adapt to complicated operation conditions under different series compensation and different wind speed of doubly-fed wind farm. Using traditional Pi control parameters can induce sub-synchronous oscillation. The simulation results show that the designed RBF neural network controller has good suppression effect on subsynchronous oscillation.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614;TM712

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