论文标题
使用二次化和平衡截断的非线性模型减少动力学电网模型
Nonlinear model reduction of dynamical power grid models using quadratization and balanced truncation
论文作者
论文摘要
在这项工作中，我们提出了一种非线性模型还原方法，用于减少两个常用的功率网格的非线性动力学模型：有效网络（EN）模型和同步电动机（SM）模型。此类模型对于电网的实时安全评估至关重要。但是，由于电网通常是大规模的，因此有必要减少模型以实时利用它们。我们将非线性功率网格模型重新制定为二次系统，并根据近似值和可观察性Gramians使用平衡的截断来减少它们。最后，我们介绍了涉及IEEE 57总线和IEEE 118总线系统的减少EN和SM模型的数值模拟的示例。
In this work, we present a nonlinear model reduction approach for reducing two commonly used nonlinear dynamical models of power grids: the effective network (EN) model and the synchronous motor (SM) model. Such models are essential in real-time security assessments of power grids. However, as power grids are often large-scale, it is necessary to reduce the models in order to utilize them in real-time. We reformulate the nonlinear power grid models as quadratic systems and reduce them using balanced truncation based on approximations of the reachability and observability Gramians. Finally, we present examples involving numerical simulation of reduced EN and SM models of the IEEE 57 bus and IEEE 118 bus systems.
