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Towards Faster Givens Rotations Based Power System State Estimator

Pandian, A and Parthasarathy, K and Soman, SA (1999) Towards Faster Givens Rotations Based Power System State Estimator. In: IEEE Transactions on Power Systems, 14 (3). pp. 837-843.


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Numerically stable and computationally efficient Power System State Estimation (PSSE) algorithms are designed using Orthogonalization (QR decomposition) approach. They use Givens rotations for orthogonalization which enables sparsity exploitation during factorization of large sparse augmented Jacobian. Apriori row; and column ordering is usually performed to reduce intermediate and and overall fills. Column ordering methods, usually based on Minimum Degree Algorithm (MDA), have matured. However, their exists a significant scope for improving the quality of row ordering. This paper introduces a new row ordering technique for Givens rotations based power system state estimators. The proposed row processing method (VPAIR) requires a shift from conventionally used row oriented QR decomposition implementation to a column oriented QR decomposition implementation. It is demonstrated that, the proposed column oriented QR decomposition algorithm which uses MD:I for column ordering and VPAIR for row ordering can lead to a, much faster PSSE. These aspects are justified by simulations on large power systems.

Item Type: Journal Article
Publication: IEEE Transactions on Power Systems
Publisher: IEEE
Additional Information: ©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Power System Statc Estimation(PSSE);Orthogonalization
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 30 Sep 2004
Last Modified: 19 Sep 2010 04:15
URI: http://eprints.iisc.ac.in/id/eprint/1614

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