双馈风电机组附加控制对轴系振荡影响的评估方法

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双馈风电机组附加控制对轴系振荡影响的评估方法

更新时间：2025-08-13

- 双馈风电机组附加控制对轴系振荡影响的评估方法
- Automation of Electric Power Systems Vol. 39, Issue 5, Pages: 34-40(2015)
- 作者机构：
  
  清华大学电机工程与应用电子技术系,北京市,100084
- 作者简介：
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- Published：2015
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WANG Lixin. [J]. Automation of electric power systems, 2015, 39(5): 34-40.
DOI：

WANG Lixin. [J]. Automation of electric power systems, 2015, 39(5): 34-40. DOI：

摘要

为消除绝对特征值灵敏度指标中参数量纲的影响

同时计及风速的概率分布特性对特征值灵敏度排序的影响

提出了一种累积相对特征值灵敏度(CRES)指标及其计算方法

并基于该指标定量评估了双馈风电机组附加控制(有功功率调制、虚拟惯性控制、下降控制、无功功率调制和机端电压控制)对机组本身轴系振荡阻尼的影响。CRES本质上是相对特征值灵敏度的加权和。通过引入相对特征值灵敏度消除了参数量纲的影响;在此基础上

按照转子运行状态将风速划分为若干区间

以平均风速作为该区间的典型风速

以风速落入该区间的概率作为该区间典型风速下计算所得相对特征值灵敏度的权重。时域仿真结果表明:基于CRES指标能有效地确定不同类型附加控制中影响轴系振荡阻尼的关键参数

通过对关键参数的重新整定可显著减小附加控制器对轴系振荡的不利影响和降低其对传动轴系统的转矩冲击。

Abstract

To eliminate the effects of parameter dimensions in the absolute eigenvalue sensitivity and account for the effects of probability distribution of wind speeds

a cumulative relative eigenvalue sensitivity (CRES) index and associated computing method is proposed. Based on CRES

impacts of various ancillary control strategies on damping torsional oscillations in the doubly-fed induction generator (DFIG)-based wind turbines can be quantitatively assessed. CRES is the sum of weighted relative eigenvalue sensitivity per se. By introducing relative eigenvalue sensitivity

the dimension of parameters can be removed. On this basis

by dividing wind speeds into several zones according to rotor operating states

the average wind speed of each zone is selected as the typical wind speed. And thus the weight of relative eigenvalue sensitivity for each zone can be determined. The method is verified through time-domain simulations. It is demonstrated that the CRES index can effectively identify key parameters

and re-tuning them can reduce the adverse influence of ancillary controllers on the torsional damping and decrease the torque impulse in the drive-train system. This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2014AA051901) and State Grid Corporation of China (No. KTB11201301545).

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