Open AccessResearch on the performance of multifrontal method in power system simulations
Author(s) -
Wenkai Zhao,
Gong Wei-zheng,
Bin Xie,
Wan Jia-Lin
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/631/4/042007
Subject(s) - computer science , factorization , matrix (chemical analysis) , matrix decomposition , power (physics) , eigenvalues and eigenvectors , parallel computing , algorithm , chemistry , physics , chromatography , quantum mechanics
Efficiency of power system simulation has close relationship to the sparse LU factorization algorithm. Multifrontal method is a notable LU factorization member. This paper investigates the performance of multifrontal method in power system simulations. Performance of multifrontal method heavily relies on the frontal matrix size. Frontal matrix size can be represented by front size. Front size is subject to the treewidth of power network. A treewidth approximation method (TAM) is presented to approximate the treewidth of power network. Two derivatives of TAM are given to tackle the sparse matrices from power flow calculation and small signal stability eigenvalue analysis respectively. Simulation results verify the accuracy and efficiency of TAM and its derivatives. Further results indicate that most power networks have low treewidth, which is prone to degrading the performance of multifrontal method. Multifrontal method is able to gain its performance in power system simulations when the front size of the involved matrix is large enough.