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The Lyapunov-based stability analysis of reduced order micro-grid via uncertain LMI condition

机译:基于不确定LMI条件的基于Lyapunov的降阶微电网稳定性分析

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This paper proposed a new three-step method for studying dynamic stability of an islanded micro-grid (MG). In conventional methods, state-space model linearization around an operating point and modal analysis are utilized. Due to lower inertia and operation of MG in islanding mode, MG is more sensitive to changes of parameters and contingencies. Therefore, small signal stability (sss) analysis has a very limited validity range and large signal studies should be also performed to get an appropriate perception of the system stability. In this paper, beside sss study to determine network stability status around a dominant operating point, an algorithm based on multi-time scale systems theory is suggested to detect slow and fast modes which can be used for system decomposition into fast and slow subsystems. Fast modes have large negative real values and/or damping ratios, which can be eliminated in large signal stability analysis with an appropriate approximation. Therefore, singular perturbation theory is used to reduce the model order and extract the network slow subsystem. Then, the Lyapunov function can be applied to reduced model. In addition, continuous load and the renewable distributed generators power variations in the system cause to wide range of changes in the operating point and state space model of the system. Therefore, the copula distribution is proposed to model the uncertainties. Then, the uncertain LMI condition based on scenarios extracted from the copula is used to determination of the Lyapunov function and the attraction domain. Finally, the attraction domain sensitivity to MG parameters change is studied to achieve sufficient insight about the system stability margins.
机译:本文提出了一种新的三步法研究孤岛微电网(MG)的动态稳定性。在常规方法中,利用围绕工作点的状态空间模型线性化和模态分析。由于较低的惯性和MG在孤岛模式下的运行,MG对参数和意外事件的变化更敏感。因此,小信号稳定性(sss)分析的有效范围非常有限,还应进行大信号研究以对系统稳定性有适当的了解。在本文中,除了进行确定主导工作点附近的网络稳定性状态的研究之外,还提出了一种基于多时标系统理论的算法来检测慢速模式和快速模式,这些模式可用于将系统分解为快速子系统和慢速子系统。快速模式具有较大的负实数值和/或阻尼比,可以通过适当的近似在大型信号稳定性分析中消除这些模式。因此,使用奇异摄动理论来降低模型阶数并提取网络慢子系统。然后,可以将李雅普诺夫函数应用于简化模型。此外,系统中的连续负载和可再生分布式发电机的功率变化会导致系统的工作点和状态空间模型发生广泛的变化。因此,提出了copula分布来对不确定性进行建模。然后,将基于从系动词中提取的场景的不确定LMI条件用于确定Lyapunov函数和吸引域。最后,研究了对MG参数变化的吸引域敏感性,以获取有关系统稳定性裕度的足够见解。

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