风电场有功控制的分布式模型预测控制

Haoran Zhao, Qiuwei Wu, C. Rasmussen, Qinglai Guo, Hongbin Sun
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引用次数: 3

摘要

本文提出了采用双分解的分布式模型预测控制器(D-MPC)对风电场的有功功率进行控制。与传统的集中式风电场控制不同,可以考虑功率参考跟踪性能和风力机负荷等多个目标,实现两者之间的权衡。此外,D-MPC基于子系统之间的通信。通过相邻子系统之间的相互作用,实现全局优化,大大减少了计算量。适用于现代大型风电场的控制。
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Distributed model predictive control for active power control of wind farm
This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D-MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can be considered to achieve a trade-off between them. Additionally, D-MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large-scale wind farm control.
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