EI-MOR: A Hybrid Exponential Integrator and Model Order Reduction Approach for Transient Power/Ground Network Analysis

Cong Wang, Dongen Yang, Quan Chen
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引用次数: 1

Abstract

Exponential integrator (EI) method has been proved to be an effective technique to accelerate large-scale transient power/ground network analysis. However, EI requires the inputs to be piece-wise linear (PWL) in one step, which greatly limits the step size when the inputs are poorly aligned. To address this issue, in this work we first elucidate with mathematical proof that EI, when used together with the rational Krylov subspace, is equivalent to performing a moment-matching model order reduction (MOR) with single input in each time step, then advancing the reduced system using EI in the same step. Based on this equivalence, we next devise a hybrid method, EI-MOR, to combine the usage of EI and MOR in the same transient simulation. A majority group of well-aligned inputs are still treated by EI as usual, while a few misaligned inputs are selected to be handled by a MOR process producing a reduced model that works for arbitrary inputs. Therefore the step size limitation imposed by the misaligned inputs can be largely alleviated. Numerical experiments are conducted to demonstrate the efficacy of the proposed method.
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EI-MOR:一种混合指数积分器和模型降阶方法用于暂态电力/地网分析
指数积分法(EI)已被证明是一种有效的加速大规模暂态电/地网络分析的方法。然而,EI要求输入在一个步骤中是分段线性的(PWL),这极大地限制了输入排列不良时的步长。为了解决这个问题,在这项工作中,我们首先用数学证明说明EI,当与有理Krylov子空间一起使用时,相当于在每个时间步中使用单个输入执行一个矩匹配模型降阶(MOR),然后在同一步中使用EI推进降阶系统。基于这种等价性,我们设计了一种混合方法EI-MOR,将EI和MOR在同一瞬态仿真中结合使用。大多数对齐良好的输入仍然像往常一样被EI处理,而一些不对齐的输入被选择由MOR过程处理,产生一个适用于任意输入的简化模型。因此,由失调输入造成的步长限制可以在很大程度上得到缓解。数值实验验证了该方法的有效性。
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