双馈感应发电机转速的非线性模型预测控制  

Nonlinear Model Predictive Control of the Speed of Double-fed Induction Generator

作　　者：刘吉宏 徐大平[2] 吕跃刚[2] 

机构地区：[1]北京电子科技职业学院自动化工程学院,北京市朝阳区100176 [2]华北电力大学控制科学与工程学院,北京市昌平区102206

出　　处：《电网技术》2011年第4期159-163,共5页Power System Technology

基　　金：国家自然科学基金项目(50677021);教育部科学技术研究重点项目(105049)~~

摘　　要：变速恒频风力发电中,双馈感应电机(double-fed induction generator,DFIG)工作在额定风速以下时,为获取最大风能,需调节发电机转速,使其迅速跟踪上不断变化的最佳转速。为减少控制参数整定的困难、减弱控制算法对DFIG模型的依赖,采用非线性模型预测控制方法实现对DFIG的转速控制。首先建立了基于最小二乘支持向量机方法的DFIG转速预测模型,然后利用粒子群优化算法进行滚动优化,最后通过预测误差进行反馈校正。试验结果表明,该方法具有较好的泛化能力和鲁棒性,动态性能和跟踪效果均比较理想。When the variable speed constant frequency doubly-fed wind turbine working below the rated wind speed, the generator speed should be adjusted to track the variational optimal speed in order to capture the maximal wind energy. In order to reduce the difficulty of control parameters integrated decision and decrease the dependence of control algorithm on the accurate mathematic model of double-fed induction generator （DFIG）, the nonlinear intelligent model predictive control algorithm was adopted to realize the speed control of DFIG. First, the predictive model of the speed of DFIG was established based on support vector machine （SVM） theory; second, the rolling optimization was solved by using particle swarm optimization （PSO） algorithm; then the close-loop control was formed by feedback correction using prediction error. The experiment results show that the control algorithm adopted in this paper has the better generalization ability and robustness, and its dynamic performance and tracking effect are alltperfect.

关 键 词：双馈感应发电机 转速控制 非线性模型预测控制 风力发电 支持向量机 最大风能捕获 

分 类 号：TM615[电气工程—电力系统及自动化]