Estimation of Piecewise-Linearized Torque Coefficient and Moment of Inertia of Windmill using Genetic Algorithm
Estimation of Piecewise-Linearized Torque Coefficient and Moment of Inertia of Windmill using Genetic Algorithm
复制标题
利用遗传算法估计风车分段线性化扭矩系数和转动惯量
DOI：
10.1541/ieejias.121.1228
复制
发表时间：
2001
影响因子：
--
通讯作者：
H. Harada
中科院分区：
文献类型：
--
作者：
Hitoshi Sori;T. Kamano;Takayuki Suzuki;T. Yasuno;H. Harada
提出了一种基于遗传算法的风力机转矩系数和转动惯量的估计方法。通常，转矩系数取决于风车的形状，并且被表示为叶尖速比的非线性函数。为了模拟非线性，转矩系数被分成m个区域，相对于叶尖速比，并在每个区域中近似为分段线性方程。将分段线性方程在各区域的增益和转动惯量作为基因，通过遗传算法进行调整，使估计的风车转速和加速度与实际值相对应。结果表明，所提出的方案的有效性估计的风车参数。
In this paper, an estimation method of both torque coefficient and moment of inertia of the windmill by using genetic algorithm is proposed. Generally, the torque coefficient is dependent on the shape of the windmill and is represented as a nonlinear function of the tip speed ratio. To simulate the nonlinearity, the torque coefficient is split into the m areas with respect to the tip speed ratio and is approximated by a piecewise linear equation in each area. The gains of the piecewise linear equation in each area and the moment of inertia are regarded as the gene and adjusted by the genetic algorithm so that the estimated windmill speed and acceleration correspond to the actual values. The results demonstrate the effective of the proposed scheme for estimation of the windmill parameters.