殷明慧;张小莲;邹云;周连俊;

• 1:南京理工大学自动化学院

摘要(Abstract)：

基于收缩跟踪区间的最大功率点跟踪控制能够改善湍流风速条件下大转动惯量风力机的风能捕获效率。但是,该方法仅依据平均风速优化设定收缩跟踪区间,忽略了湍流强度、风力机的某些气动、结构参数(如最佳叶尖速比、转动惯量等)等其它影响因素。考虑到跟踪区间优化设定与多种因素存在难以解析描述的复杂关系,提出了一种运用径向基函数神经网络优化跟踪区间的最大功率点跟踪控制。该改进方法以平均风速和湍流强度作为神经网络的输入变量,以具体风力机仿真数据作为训练样本,以补偿系数作为神经网络的输出变量。从而使得跟踪区间的优化设定不仅能够考虑变化的风速条件,而且能同时反映具体风力机的气动、结构设计。最后,对模拟风速序列进行了仿真计算与比较分析,验证了该方法的有效性和优越性。

关键词(KeyWords)： 风力发电;最大功率点跟踪;收缩跟踪区间;神经网络

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(61203129,61174038,61104064);; 中国博士后科学基金资助项目(2013M541674)~~

作者(Author): 殷明慧;张小莲;邹云;周连俊;

Email:

DOI: 10.13335/j.1000-3673.pst.2014.08.025

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