高低风速下大规模风电场功率爬坡有限度控制策略研究

发布时间：2019-05-11 13:31

【摘要】：随着全球经济的急速发展,电力需求和对节能减排的要求日益提高,风能作为一种最具商业价值的可再生能源越来越受到各国重视。风电场功率爬坡作为风电不确定性和波动性的典型事件,对电网稳定性的影响巨大。本文以大规模风电场功率爬坡事件为研究对象,对大规模风电场功率爬坡优化控制策略进行研究,主要研究工作如下:简述了风力发电机技术的基础理论,建立了双馈感应风电机组数学模型与风电场数学模型。针对低风速工况下未引起切机的风电场功率爬坡过程,提出了一种低风速下风电场功率爬坡优化控制策略。利用带精英策略的非支配排序的遗传算法对风电场功率爬坡曲线进行优化,得到了兼顾爬坡率与弃风量的功率参考曲线,通过双馈感应发电机变流器与变桨距角相结合的反馈控制方式,使风电场输出功率曲线跟踪参考曲线。在MATLAB/Simulink环境下进行仿真算例计算分析,验证了低风速工况下风电场功率爬坡控制策略的有效性和优越性。针对高风速工况下含切机的风电场功率爬坡过程,提出了一种高风速下含切机过程的风电场功率爬坡优化控制策略。利用带精英策略的非支配排序的遗传算法对功率爬坡曲线进行优化,得到了切机过程的参考曲线。根据风电场中各台机组的不同风速特性与故障率,首次提出了预切机优先度系数,同时计算出各台风机的切机时间节点,依据优先度系数的大小顺序与时间节点逐次切机,使风电场整体的输出功率曲线跟踪优化所得的参考曲线,以减弱高风速下风电机组切机造成的功率剧烈波动。利用RTDS实时仿真平台与DSP物理控制器,搭建了半物理仿真系统并进行了半物理实验。实验结果验证了本文所提出的控制策略的正确性和有效性。
[Abstract]:With the rapid development of the global economy, the demand for electricity and the requirements for energy conservation and emission reduction are increasing day by day. Wind energy, as one of the most commercially valuable renewable energy sources, has been paid more and more attention by many countries. As a typical event of wind power uncertainty and volatility, wind farm power climbing has a great impact on the stability of power grid. Taking the power climbing event of large-scale wind farm as the research object, this paper studies the optimal control strategy of large-scale wind farm power climbing. The main research work is as follows: the basic theory of wind turbine technology is briefly described. The mathematical model of doubly-fed induction wind turbine and the mathematical model of wind farm are established. Aiming at the power climbing process of wind farm without cutting machine under low wind speed, an optimal control strategy for wind farm power climbing under low wind speed is proposed. The power climbing curve of wind farm is optimized by using the genetic algorithm with elite strategy, and the power reference curve is obtained, which takes into account both the climbing rate and the abandoned air volume. Through the feedback control mode of doubly-fed induction generator converter and variable pitch angle, the output power curve of wind farm can track the reference curve. A simulation example is carried out in MATLAB/Simulink environment to verify the effectiveness and superiority of the power climbing control strategy for wind farm under the condition of low wind speed. Aiming at the power climbing process of wind farm with cutting machine under high wind speed, an optimal control strategy for wind farm power climbing process with cutting machine under high wind speed is proposed in this paper. The undominated sorting genetic algorithm with elite strategy is used to optimize the power climbing curve, and the reference curve of cutting process is obtained. According to the different wind speed characteristics and failure rate of each unit in the wind farm, the priority coefficient of the pre-cutting machine is put forward for the first time, and the cutting time node of each fan is calculated at the same time. According to the order of the priority coefficient and the time node, The output power curve of the wind farm as a whole tracks the optimized reference curve in order to reduce the sharp fluctuation of the power caused by the cutting of the wind turbine under high wind speed. Using RTDS real-time simulation platform and DSP physical controller, a semi-physical simulation system is built and semi-physical experiments are carried out. The experimental results verify the correctness and effectiveness of the control strategy proposed in this paper.
【学位授予单位】：上海电机学院
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614

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