并行稀疏系统直接求解库SuperLU_MT在状态估计中的应用

CHEN Quanwei

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并行稀疏系统直接求解库SuperLU_MT在状态估计中的应用

更新时间：2025-08-13

- 并行稀疏系统直接求解库SuperLU_MT在状态估计中的应用
- Automation of Electric Power Systems Vol. 41, Issue 3, Pages: 83-88(2017)
- 作者机构：
  
  河海大学可再生能源发电技术教育部工程研究中心,江苏省,南京市,210098
- 作者简介：
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- Published：2017
- 稿件说明：
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CHEN Quanwei. [J]. Automation of electric power systems, 2017, 41(3): 83-88.
DOI：

CHEN Quanwei. [J]. Automation of electric power systems, 2017, 41(3): 83-88. DOI：

摘要

利用基于超节点LU分块分解算法、列消去树和多核多线程并行计算原理的并行稀疏系统直接求解库SuperLU_MT实现电力系统状态估计，主要在求解迭代方程、不良数据检测辨识环节调用SuperLU_MT实现加速。通过对电气与电子工程师协会(IEEE)测试系统以及实际电网算例验证，表明通用的并行稀疏系统直接求解库适用于电力系统状态估计，能够获得较显著的并行计算效果，在多核计算机上缩短了状态估计的计算时间。

Abstract

The library of SuperLU_MT based on the use of the super node LU decomposition block algorithm

column elimination trees

multi-core and multi-threaded parallel computing theory

is used to develop electric power system state estimation. To achieve acceleration

the interface of SuperLU_MT is called mainly in the solution of the iterative equation

the bad data detection and identification. The validity of the algorithm is verified by the Institute of Electrical and Electronic Engineers(IEEE)test power system and an actual power system

which indicates that the parallel sparse system direct solver library is suitable for state estimation of power systems. It will significantly reduce state estimation computation time on multicore computers.

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