潮流计算和偶然性分析中求解Ax=b系统的直接和迭代方法的关键评价

A. Alves, E. Asada, A. Monticelli
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引用次数: 32

摘要

研究比较了Ax=b系统的直接求解和迭代求解的性能。通过直接方法,我们指的是基于稀疏性保持高斯消去的方法,而通过迭代方法,我们指的是预条件共轭梯度方法,例如基于矩阵A的不完全分解的方法(例如,不完全Cholesky和K/sub 0/预条件)。提出了一种新的排序方案,减少了迭代方法达到收敛所需的迭代次数,并针对偶然性筛选问题提出了一种替代条件法。在14至1663个总线的网络上进行了测试,包括基本情况和应急情况。
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Critical evaluation of direct and iterative methods for solving Ax=b systems in power flow calculations and contingency analysis
Studies comparing the performance of direct and iterative solvers of Ax=b systems have been performed. By direct methods we mean sparsity preserving Gaussian elimination based approaches, whereas by iterative methods we mean pre-conditioned conjugate gradient methods such as the ones based on incomplete factorization of matrix A (e.g., incomplete Cholesky and K/sub 0/ pre-conditioners). A new ordering scheme has been developed which decreases the number of iterations required by iterative methods to reach convergence and an alternative conditioning approach is suggested in connection with the contingency screening problem. Tests have been performed with networks varying from 14 to 1663 buses, including base-case and contingency cases.
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