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Drivetrain fatigue strength characteristics of model‐predictive control for wind turbines
Wind Energy ( IF 4.0 ) Pub Date : 2020-09-22 , DOI: 10.1002/we.2520
Carsten Schulz 1 , Colin Schwarz 1
Affiliation  

Wind turbines play a crucial role in the revolution towards renewable resources. They need to be economically competitive to be sustainable. This still requires to lower the cost of energy (COE). To this end, nonlinear model predictive control (NMPC) is used within this paper. As known from literature, NMPC significantly improves the energy extracting performance as well as the mitigation of tower loads of wind turbines. As it is shown in this paper, the drivetrain fatigue strength drops disproportionally in parallel, which either increases the demands on the turbine design or decreases the lifetime of drivetrain components. Without additional boundary conditions to the underlying optimal control problems (OCPs), the application of energy‐maximizing NMPC might so even raise the COE. Only penalizing axial torque oscillations by quadratic terms decreases energy‐extracting performance below the level of classical wind turbine controllers. This makes more sophisticated conditions necessary. In this paper, the increase of the drivetrain damage by NMPC is analyzed, and appropriate boundary conditions are derived, to balance the two contradicting objectives of energy maximization and drivetrain load mitigation. An NMPC approach based on indirect methods is used, to obtain a solution of the OCPs very efficiently. It applies the Hamilton equations and Pontryagin's maximum principle. Its accuracy and efficiency to solve OCPs was presented over the last decades.

中文翻译:

风力发电机模型预测控制的动力总成疲劳强度特性

风力涡轮机在向可再生资源的革命中起着至关重要的作用。他们需要在经济上具有竞争力才能保持可持续性。这仍然需要降低能源成本(COE)。为此,本文使用了非线性模型预测控制(NMPC)。从文献中知道,NMPC显着提高了能量提取性能以及减轻了风轮机的塔架负荷。如本文所示,传动系统的疲劳强度平行地成比例地下降,这要么增加了对涡轮机设计的要求,要么缩短了传动系统组件的使用寿命。如果没有潜在的最佳控制问题(OCP)的附加边界条件,则应用能量最大化的NMPC可能甚至会提高COE。仅用二次项惩罚轴向转矩振荡会降低能量提取性能,使其低于传统风力涡轮机控制器的水平。这使得需要更复杂的条件。本文分析了NMPC对动力传动系统造成的损害的增加,并推导了适当的边界条件,以平衡能量最大化和降低动力传动系统负载这两个相互矛盾的目标。使用基于间接方法的NMPC方法,可以非常有效地获得OCP的解决方案。它应用了Hamilton方程和Pontryagin的最大原理。在过去的几十年中,它提出了解决OCP的准确性和效率。分析了NMPC对动力传动系统造成的损害的增加,并推导了适当的边界条件,以平衡能量最大化和减轻动力传动系统负载这两个相互矛盾的目标。使用基于间接方法的NMPC方法,可以非常有效地获得OCP的解决方案。它应用了汉密尔顿方程和庞特里亚金的最大原理。在过去的几十年中,它提出了解决OCP的准确性和效率。分析了NMPC对动力传动系统造成的损害的增加,并推导了适当的边界条件,以平衡能量最大化和减轻动力传动系统负载这两个相互矛盾的目标。使用基于间接方法的NMPC方法,可以非常有效地获得OCP的解决方案。它应用了Hamilton方程和Pontryagin的最大原理。在过去的几十年中,它提出了解决OCP的准确性和效率。
更新日期:2020-11-06
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