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Negative Reactance Impacts Power Flow Convergence Using Conjugate Gradient Method
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DOI：10.1109/TCSII.2019.2953107.png)
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Abstract
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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.
Keywords:
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)
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