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Disturbance observer-based decentralised power tracking control of wind farms

机译:基于干扰观测器的风电场分散功率跟踪控制

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摘要

Wind farm normally involves a large number of wind turbines that are interactive due to air flow influence, making it interesting yet challenging to design a decentralised control scheme for each turbine unit so that stable power generation of wind farm is achieved. In this study, a decentralised adaptive control scheme is proposed for interconnected wind power generation systems in the presence of uncertain interaction among the turbines, capturing the maximum possible wind power. Based upon the disturbance observer technique, the unknown compounded disturbance is estimated. A speed function contributing to the decentralised control solution is introduced to improve the transient behaviour of the power tracking during the main course of the system operation so that the tracking error converges to a preassigned arbitrarily small compact set with a prescribed rate of convergence in a given finite time. The effectiveness of the proposed neuroadaptive tracking control strategy is verified through numerical simulation.
机译:风电场通常包含大量由于气流影响而相互影响的风力涡轮机,这使得为每个涡轮机单元设计分散控制方案以实现稳定的风力发电变得有趣而具有挑战性。在这项研究中,提出了一种分散式自适应控制方案,该方案适用于在风力涡轮机之间存在不确定相互作用的情况下互连风力发电系统,以捕获最大可能的风力。基于干扰观测器技术,估计未知的复合干扰。引入了有助于分散控制解决方案的速度函数,以改善系统操作主要过程中功率跟踪的瞬态行为,从而使跟踪误差收敛到给定的任意小紧凑集,并且在给定的收敛速率下有限的时间。通过数值仿真验证了所提出的神经自适应跟踪控制策略的有效性。

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