基于气动功率与发电机功率目标的风力机转矩控制器极值搜索控制优化分析
Analysis of extremum seeking control for wind turbine torque controller optimization by aerodynamic and generator power objectives
AI总结：
针对风力机退化导致固定参数控制器性能劣化的问题，本文分析了分别以气动功率和发电机功率为目标的ESC转矩增益优化的差异，指出发电机功率目标存在收敛速率限制，并提出基于气动功率估计构建目标的解决方案。
摘要：
风力机会随时间发生性能退化，导致其结构特性、气动弹性特性以及气动特性发生变化。相比之下，风力机控制器的校准参数通常保持恒定，这会导致系统性能达不到最优，甚至可能引发稳定性问题。因此，风力机控制器参数的校准工作受到了广泛关注。针对这一问题，现有文献中已经提出了多种基于极值搜索控制（extremum seeking control, ESC）的自适应控制方案，这些方案已被成功应用于通过优化$Kω^2$型转矩控制器来最大化风力机的能量捕获。在实际应用中，ESC通常采用易于获取的发电机电功率作为优化目标。本文分析了分别以气动功率和发电机功率为目标进行转矩增益优化的可行性。研究表明，与气动功率目标不同，采用发电机功率目标时，必须将抖振频率限制在较低范围内，这会降低收敛速度，除非对ESC解调信号的相位进行适当调整。对两种系统的频域分析显示，二者具有截然不同的相位特性，这会直接影响ESC的性能。本文还提出了一种解决方案，即基于气动功率的估计值构建优化目标度量。
英文摘要：
Wind turbines degrade over time, resulting in varying structural, aeroelastic, and aerodynamic properties. In contrast, the turbine controller calibrations generally remain constant, leading to suboptimal performance and potential stability issues. The calibration of wind turbine controller parameters is therefore of high interest. To this end, several adaptive control schemes based on extremum seeking control (ESC) have been proposed in the literature. These schemes have been successfully employed to maximize turbine power capture by optimization of the $Kω^2$-type torque controller. In practice, ESC is performed using electrical generator power, which is easily obtained. This paper analyses the feasibility of torque gain optimization using aerodynamic and generator powers. It is shown that, unlike aerodynamic power, using the generator power objective limits the dither frequency to lower values, reducing the convergence rate unless the phase of the demodulation ESC signal is properly adjusted. A frequency-domain analysis of both systems shows distinct phase behavior, impacting ESC performance. A solution is proposed by constructing an objective measure based on an estimate of the aerodynamic power.
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