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Optimal control of wind farms for fatigue load minimization

机译:风电场的最优控制,以最大程度地降低疲劳负荷

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In this paper, we introduce a distributed control methodology that enables wind generators (WGs) to dynamically dispatch and regulate their power outputs to optimal equilibria in real-time. These equilibria are constructed such that the total mechanical fatigue loads experienced by WGs are minimized and a total assigned power demand is collectively met. We begin by posing the fatigue-load minimization constrained optimal control problem (FLMCOC) as a restricted agreement problem and then propose a fully distributed control methodology for recovering its solution that leverages a particular consensus+innovations algorithm. The distributed algorithm can be realized via any arbitrary peer-to-peer communication network and under any case, it can guarantee dynamic regulation of WGs' power outputs to their optimal values. Collectively, this paper offers a distributed control methodology for attaining a solution to the FLMCOC problem for large-scale wind farms that is computationally efficient, scalable, resilient to single-point communication or agent failures and privacy preserving. The proposed control methodology is validated through numerical simulations on the modified IEEE 24-bus power network.
机译:在本文中,我们介绍了一种分布式控制方法,该方法可使风力发电机(WG)实时动态调度和调节其功率输出,以达到最佳平衡。构造这些平衡点是为了使工作组承受的总机械疲劳负载最小化,并共同满足总的分配功率需求。我们首先将疲劳负荷最小化约束最优控制问题(FLMCOC)视为受限协议问题,然后提出一种完全分布式的控制方法,以利用特定的共识+创新算法来恢复其解决方案。分布式算法可以通过任意的对等通信网络实现,并且在任何情况下都可以保证将工作组的功率输出动态调节到最佳值。总体而言,本文提供了一种分布式控制方法,可为大型风电场实现FLMCOC问题的解决方案,该解决方案计算效率高,可扩展,可抵抗单点通信或代理故障和隐私保护。通过对改进的IEEE 24总线电力网络进行数值模拟,验证了所提出的控制方法。

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