大型风电机组功率跟踪优化控制策略研究

发布时间：2019-01-04 13:10

【摘要】：作为可再生清洁能源,风力发电的重要性与日俱增。由于自然风具有较强的随机性,使得风电机组的控制难度大大增加,因此传统的控制策略在运行中难以跟踪最大功率点,浪费了一部分风能。如何提高风能利用系数,实现发电量最大化已经成为了风力发电研究中的关键问题。本文以双馈风力发电机组为对象,研究了快速变化风速激励下的最大功率跟踪(MPPT)控制策略。研究内容包括:针对传统控制策略中有效风速难以获得的问题,基于高阶容积卡尔曼滤波(HCKF)和牛顿-拉夫逊方法(NR)设计了有效风速估计器。为了进一步提高HCKF方法对测量过程中粗差的抵抗能力,将经典的抗差估计理论与HCKF方法相结合,提出了一种抗差HCKF方法并应用到有效风速估计器中。定义了以非奇异快速终端滑模(NFTSMC)为基础的转速控制器和电流控制器,并对控制器的稳定性进行了证明,同时针对转速环容易产生抖振的问题,使用非线性跟踪-微分器对系统的不确定性进行估计并对其实时补偿,以削弱系统抖振,仿真结果表明所设计的控制器可以满足最大风能跟踪的要求。针对标准果蝇算法在全局范围内搜索能力不均匀所导致的问题,提出了一种步长改进策略,在寻优过程中根据当前果蝇群体中最优个体位置,动态的对果蝇前进步长进行调整,使果蝇算法能够平衡在全局范围内的搜索能力。通过几种经典测试函数对步长改进策略进行了测试,结果表明:在保证寻优成功率的同时,步长改进策略使果蝇算法的收敛速度和精度均得到提升。进一步通过改进果蝇算法对控制器参数进行了寻优,仿真结果表明寻优所得参数与经验参数相比具有更好的动态特性。以双馈风电机组作为研究对象,在快速变化风速激励下,对风电机组的动态响应进行了仿真研究,结果表明本文所提出的控制策略可以准确估计有效风速,与传统控制策略相比可以更好的实现最大功率跟踪。
[Abstract]:As a renewable clean energy, wind power generation is becoming increasingly important. Due to the strong randomness of the natural wind, the difficulty of wind turbine control is greatly increased, so the traditional control strategy is difficult to track the maximum power points in operation, and waste part of wind energy. How to improve the utilization coefficient of wind energy and maximize the power generation has become a key problem in wind power generation research. In this paper, the maximum power tracking (MPPT) control strategy of a doubly-fed wind turbine is studied under the excitation of rapidly varying wind speed. The research contents include: aiming at the difficulty of obtaining effective wind speed in traditional control strategy, an effective wind speed estimator is designed based on high-order volumetric Kalman filter (HCKF) and Newton-Raphson method (NR). In order to further improve the resistance of HCKF method to gross error in the measurement process, a robust HCKF method is proposed and applied to the effective wind speed estimator by combining the classical robust estimation theory with the HCKF method. The speed controller and current controller based on the nonsingular fast terminal sliding mode (NFTSMC) are defined, and the stability of the controller is proved. The nonlinear tracking-differentiator is used to estimate the uncertainty of the system and compensate it in real time in order to weaken the chattering of the system. The simulation results show that the controller designed can meet the requirements of maximum wind energy tracking. Aiming at the problem caused by the uneven searching ability in the global scope of the standard Drosophila algorithm, an improved step size strategy is proposed, which dynamically adjusts the forward step size of Drosophila according to the optimal individual position in the current Drosophila population. So that the Drosophila algorithm can balance the search ability in the global scope. Several classical test functions are used to test the step size improvement strategy. The results show that the improved step size strategy can improve the convergence speed and precision of Drosophila algorithm while ensuring the success rate of optimization. Furthermore, the controller parameters are optimized by the improved Drosophila algorithm. The simulation results show that the optimized parameters have better dynamic characteristics than the empirical parameters. Taking doubly-fed wind turbine as the research object, the dynamic response of wind turbine is simulated under the excitation of rapidly changing wind speed. The results show that the control strategy proposed in this paper can accurately estimate the effective wind speed. Compared with the traditional control strategy, it can achieve the maximum power tracking better.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM315

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