正交稀疏向量法(电力系统应用)

N. Vempati, I. Slutsker, W. Tinney
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引用次数: 0

摘要

稀疏向量法提高了基于三角分解的电网方程求解速度。到目前为止,这些方法还没有与最小二乘状态估计最稳定的正交分解方法一起使用。给出了稀疏向量法扩展到给定旋转的解释,这是最适合于电力系统状态估计的正交化形式。这些方法可以从几个方面提高正交估计算法的速度。它们的优势在现实生活网络中得到了体现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orthogonal sparse vector methods (power system applications)
Sparse vector methods speed up solutions of power network equations based on triangular factorization. Until now, these methods have not been used with orthogonal factorization, the most numerically stable method for least squares state estimation. An explanation is given for the extension of sparse vector methods to Givens rotations, the form of orthogonalization most suitable for power system state estimation. The methods can speed up orthogonal estimation algorithms in several ways. Their advantages are demonstrated on real-life networks.<>
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