Multidimensional Variability Analysis of Complex Power Distribution Networks via Scalable Stochastic Collocation Approach
Multidimensional Variability Analysis of Complex Power Distribution Networks via Scalable Stochastic Collocation Approach
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DOI：
10.1109/tcpmt.2015.2477717
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发表时间：
2015-10
期刊：
影响因子：
--
通讯作者：
A. Prasad;Sourajeet Roy
中科院分区：
文献类型：
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作者：
A. Prasad;Sourajeet Roy
提出了一种新的SPICE兼容随机配置法，用于复杂不规则配电网的变异性分析。所提出的方法依赖于斯特劳德体积规则，用于在需要执行PDN的确定性SPICE模拟的多维随机空间中定位稀疏配置节点集。与传统的非侵入式多项式混沌方法所表现出的指数或多项式尺度不同，所提出的Stroud体积方法的主要优点是所需的配置节点的数目与随机维度的数目成线性关系，从而显著地提高了模拟速度。通过多个数值算例验证了该方法对单层和多层具有孔/孔、窄缝和不规则几何结构的PDN的有效性。
This paper presents a novel SPICE-compatible stochastic collocation approach for the variability analysis of complex and irregular-shaped power distribution networks (PDNs). The proposed methodology relies on the Stroud cubature rules for locating the sparse set of collocation nodes within the multidimensional random space where the deterministic SPICE simulation of the PDN needs to be performed. The key advantage of the proposed Stroud cubature approach is that the number of collocation nodes required scales linearly with the number of random dimensions as opposed to the exponential or polynomial scaling exhibited by the conventional nonintrusive polynomial chaos approaches, thereby resulting in significantly faster simulations. The validity of the proposed approach for both single-layered and multilayered PDNs characterized by holes/apertures, narrow slots, and irregular geometries is established through multiple numerical examples.