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Efficient High-Order Participation Factor Computation via Batch-Structured Tensor Contraction

delete2025-11-10
delete0
PRE
AI
M
Mahsa Sajjadi
K
Kaiyang Huang
K
Kai Sun
DOI：10.1109/TPWRS.2025.3631327delete
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摘要

摘要

En 中文
参与因子（PFs）量化了系统模态与状态变量之间的相互作用，并在模态分析、模型降阶和控制设计等众多应用中发挥着关键作用。随着系统复杂性的增加，特别是由于电力电子设备和可再生能源集成的影响，对可扩展的高阶非线性参与因子（NPF）计算的需求变得更加迫切。本文提出了一种高效的基于张量的方法，用于计算任意阶的NPF。传统上直接从正规形理论计算PFs的方法计算成本高昂——即使是二阶PFs也是如此——并且由于内存限制，对于更高阶的情况变得不可行。为解决这一问题，引入了一种基于张量收缩的方法，该方法能够通过批处理策略计算高阶PFs。批处理大小根据可用的计算资源动态确定，从而实现可扩展且内存高效的计算。
Keyword:
Participation factors
tensor contraction
nonlinear modal analysis
Taylor series expansion

期刊

IEEE Transactions on Power Systems 封面图
IEEE Transactions on Power Systems
IF:
7.2
论文数:
1.1W
被引数:
5.0W

机构

U
University of Tennessee
学者数:
1.8K
论文数: 960
被引数: 3.0W
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