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Accurate Consensus-Based Distributed Averaging With Variable Time Delay in Support of Distributed Secondary Control Algorithms

机译:基于准确的基于共识的分布式平均,具有用于分布式二级控制算法的可变时间延迟

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Distributed secondary control has been widely used in hierarchical control structures, where multiple distributed generators (DGs) need to coordinate to regulate system voltage and frequency. In these systems, consensus algorithms determine the average of a group of dynamic states (e.g., voltages measured by a group of DGs). To be useful, consensus algorithms must be computationally efficient, stable and accurate. In practice, numerous practical implementation challenges significantly affect the consensus equilibrium. In this paper, we quantify the accuracy deviations of the distributed average observer algorithms proposed in the literature to demonstrate the problems with the state-of-the-art distributed averaging techniques. A novel approach is proposed that achieves accurate average tracking in the presence of time-varying communication delays among agents. In our implementation, time synchronization of all distributed controllers is enabled by a novel software platform, called Resilient Information Architecture Platform for the Smart Grid (RIAPS). The proposed distributed average observer is implemented on hardware controllers and its effectiveness is validated in a controller hardware-in-the-loop testbed.
机译:分布式次级控制已广泛用于分层控制结构,其中多个分布式发电机(DGS)需要坐标以调节系统电压和频率。在这些系统中,共识算法确定一组动态状态的平均值(例如,由一组DG测量的电压)。要有用,必须达成共识算法,必须计算高效,稳定和准确。在实践中,众多实际实施挑战显着影响了均衡的共识平衡。在本文中,我们量化了文献中提出的分布式平均观察者算法的准确性偏差,以展示最先进的分布平均技术的问题。提出了一种新方法,以实现在代理之间的时变通信延迟存在的情况下实现准确的平均跟踪。在我们的实现中,新颖的软件平台使所有分布式控制器的时间同步称为智能电网(RIAPS)的弹性信息架构平台。所提出的分布式平均观察者在硬件控制器上实现,其有效性在控制器硬件测试用符中验证。

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