摘要
由于风力发电系统具有非线性和参数时变等特点,其控制器参数在设计和优化时不易计算与整定。利用Bladed软件中模型线性化结合模型降阶算法建立了适用于参数整定的机组线性化模型,应用免疫记忆粒子群算法整定控制器PI(Proportion Integral)参数,并基于Bladed参数辨识结果计算了最优转速-转矩控制的增益系数和自适应PI变桨距控制的增益因子,形成了一种基于Bladed的风电机组变速与变桨距控制器参数优化方法。仿真结果表明了该优化方法的正确性和有效性。
Due to nonlinearity and time-varying parameters of wind power system, its controller parameters are hard to be calculated and tuned during the process of design and optimization. The linear model which is suitable for parameters tuning was built through model linearization of Bladed and model reducing-order algorithm. The PI parameter was tuned with the IM-PSO （Immune Memory Particle Swarm Optimization）. Moreover, the gain coefficient of optimal torque control and the gain divisor of adaptive PI pitch control conducted optimizing calculation based on the identification parameters of Bladed. A set of optimization method .for variable speed and pitch controller of wind turbine was established. The simulation results show the validity and advantages of the proposed methods.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2016年第7期1644-1650,1660,共8页
Journal of System Simulation
基金
中央高校基本科研业务费(2015MS24)
