Negative Reactance Impacts Power Flow Convergence Using Conjugate Gradient Method

被引:1
作者
Ding, Tao [1 ]
Qu, Ming [1 ]
Bai, Jiawen [1 ]
Li, Fangxing [2 ]
机构
[1] Xi An Jiao Tong Univ, Sch Elect Engn, Xian 710049, Peoples R China
[2] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN 37596 USA
基金
中国国家自然科学基金;
关键词
Load flow; Eigenvalues and eigenfunctions; Linear systems; Transmission line matrix methods; Convergence; Power grids; Negative reactance; graph theory; Laplacian matrix; fast decoupled power flow; conjugate gradient (CG); SYSTEMS; SOLVER;
D O I
10.1109/TCSII.2019.2953107
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
It is usually considered in power systems that the B matrices in fast decoupled power flow (Bx2019; and Bx201D;) are symmetric and positive-definite. The fast decoupled power flow (FDPF) based on the conjugate gradient (CG) iterative method was well developed, because the CG iterative method has a good convergence property and a lower memory requirement which can be easily implemented in the parallel computation. However, a rare yet important phenomenon hasnx2019;t been well addressed in that x201C;negative reactancex201D; may exist in the practical power system models, which could affect the definiteness of B matrices in FDPF and the CG convergence performance. In this brief, the eigenvalues of B matrices with negative reactance are investigated and the convergence of CG for FDPF is discussed. Several large-scale practical systems are tested, which could provide some insights for the study of the FDPF using the CG method with negative reactances.
引用
收藏
页码:2527 / 2531
页数:5
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