基于支持向量机和微分进化算法的风电机优化运行

风电机出力控制是风电场运行过程中的一个关键问题。针对风电机出力与风速和桨距角之间存在非常复杂的关系,很难建立通用准确的数学模型,提出了一种新的风电机出力优化模式,即首先通过支持向量机算法建立风电机出力与运行参数之间的非线性拟合模型,并基于此模型和风速的变化,采用高效的微分进化算法对风力机桨距角进行快速动态优化,从而实现风电机出力最大化。以鄱阳湖长岭风电场风电机组实际运行数据进行了仿真应用与分析。结果表明通过优化风力机桨距角可有效地提高风电机出力,验证了文中方法的可行性和优越性。采用文中方法可准确建立风速与最优桨距角的动态对应关系,为风电机的优化运行提供了科学的指导。

Optimal Operation of Wind Turbines Based on Support Vector Machine and Differential Evolution Algorithm

Output control of wind turbines is the key item in the operation of wind farm.In view of complicated relations among wind turbine output,wind speed and blade pitch angle,it is hard to establish a versatile and accurate mathematical model.For this reason,a new mode to optimize wind turbine output is proposed: firstly a model for nonlinear fitting between wind turbine output and operational parameters is built;then based on the built model and the variation of wind speed and adopting the high-efficient differential evolution algorithm,the blade pitch angle of wind turbine is optimized fast and dynamically.Using the proposed method,the dynamic relation between wind speed and optimal blade pitch angle can be established.Simulation results of the proposed method show that the output of wind turbine can be effectively uprated,thus the feasibility of the proposed method is verified.