The Experts below are selected from a list of 429 Experts worldwide ranked by ideXlab platform

K Parthasarathy - One of the best experts on this subject based on the ideXlab platform.

  • variable Pivot column oriented givens rotations based power system state estimator
    International Journal of Electrical Power & Energy Systems, 1998
    Co-Authors: A Pandian, S A Soman, K Parthasarathy
    Abstract:

    The numerically stable power system state estimation (PSSE) algorithm uses a Givens rotations based least square (LS) solver. Row and column ordering techniques are used to reduce computations as well fills arising during sparse matrix QR decomposition. Row oriented algorithm is popularly used for QR decomposition in PSSE application with a priori Row and column ordering to reduce fills. This paper proposes online variable Pivot Row and column ordering techniques for sparse QR decomposition, which locally reduce fills during each rotation operation. Use of online ordering techniques requires a shift from Row oriented QR decomposition to column oriented QR decomposition. Simulation results on large power systems demonstrate the benefits of the proposed approach in comparison to Row oriented QR decomposition.

István Maros - One of the best experts on this subject based on the ideXlab platform.

  • A Piecewise Linear Dual Phase-1 Algorithm for the Simplex Method with All Types of Variables
    2009
    Co-Authors: István Maros
    Abstract:

    A dual phase-1 algorithm for the simplex method that handles all types of variables is presented. In each iteration it maximizes a piecewise linear function of dual infeasibilities in order to make the largest possible step towards dual feasibility with a selected outgoing variable. The new method can be viewed as a generalization of traditional phase-1 procedures. It is based on the multiple use of the expensively computed Pivot Row. By small amount of extra work per iteration, the progress it can make is equivalent to many iterations of the traditional method. In addition to this main achievement it has some further important and favorable features, namely, it is very efficient in coping with degeneracy and numerical difficulties. Both theoretical and computational issues are addressed. Examples are also given that demonstrate the power and flexibility of the method

  • A Piecewise Linear Dual Phase-1 Algorithm for the Simplex Method
    Computational Optimization and Applications, 2003
    Co-Authors: István Maros
    Abstract:

    A dual phase-1 algorithm for the simplex method that handles all types of variables is presented. In each iteration it maximizes a piecewise linear function of dual infeasibilities in order to make the largest possible step towards dual feasibility with a selected outgoing variable. The algorithm can be viewed as a generalization of traditional phase-1 procedures. It is based on the multiple use of the expensively computed Pivot Row. By small amount of extra work per iteration, the progress it can make is equivalent to many iterations of the traditional method. While this is its most important feature, it possesses some additional favorable properties, namely, it can be efficient in coping with degeneracy and numerical difficulties. Both theoretical and computational issues are addressed. Some computational experience is also reported which shows that the potentials of the method can materialize on real world problems.

A Pandian - One of the best experts on this subject based on the ideXlab platform.

  • variable Pivot column oriented givens rotations based power system state estimator
    International Journal of Electrical Power & Energy Systems, 1998
    Co-Authors: A Pandian, S A Soman, K Parthasarathy
    Abstract:

    The numerically stable power system state estimation (PSSE) algorithm uses a Givens rotations based least square (LS) solver. Row and column ordering techniques are used to reduce computations as well fills arising during sparse matrix QR decomposition. Row oriented algorithm is popularly used for QR decomposition in PSSE application with a priori Row and column ordering to reduce fills. This paper proposes online variable Pivot Row and column ordering techniques for sparse QR decomposition, which locally reduce fills during each rotation operation. Use of online ordering techniques requires a shift from Row oriented QR decomposition to column oriented QR decomposition. Simulation results on large power systems demonstrate the benefits of the proposed approach in comparison to Row oriented QR decomposition.

Fang Wan-liang - One of the best experts on this subject based on the ideXlab platform.

  • Block QR decomposition based power system state estimation algorithm
    Electric Power Systems Research, 2005
    Co-Authors: Du Zhengchun, Niu Zhenyong, Fang Wan-liang
    Abstract:

    This paper presents a new approach for the solution of the equality constrained power system state estimation problem. Virtual measurements are treated as equality constraints to avoid the numerical ill-conditioning problem due to the disparity in weighting factors. Triangular factorization of the coefficient matrix is carried out by performing QR decomposition on two partitioned matrices and by solving a linear equations set involving a sparse triangular matrix. Compared with normal equations with constraints method, the proposed method circumvents the cross product of the Jacobian matrix, which can cause the loss of information. In sparse QR decomposition based on Givens transformation, variable Pivot Row and column ordering techniques are used to reduce fill-ins and then computation efficiency is enhanced. Simulation results have shown that proposed method is stable and robust.

  • A BLOCK QR BASED POWER SYSTEM STATE ESTIMATION ALGORITHM
    2003
    Co-Authors: Fang Wan-liang
    Abstract:

    This paper presents a stable block QR based method for solving power system state estimation problem. In the proposed method, virtual measurements are treated as equality constraints, which avoids the numerical ill-conditioning problem due to the disparity in weighting factors. At each iteration, triangular factorization of the coefficient matrix is carried out by performing QR decomposition on two partitioned matrices and by solving a set of linear equations involving a sparse triangular matrix. Compared with normal equations with constraints (NE/C) method, the proposed method circumvents the cross production of the Jacobian matrix which can cause the loss of information. And this method ensures the numerical stability of decomposition. In sparse QR decomposition based on Givens transformation, variable Pivot Row and column ordering techniques are used to reduce fill-ins and then computation efficiency is enhanced. Simulation results have shown that proposed method is stable and robust. Furthermore, it is very efficient and can meet the need of online state estimation.

S A Soman - One of the best experts on this subject based on the ideXlab platform.

  • variable Pivot column oriented givens rotations based power system state estimator
    International Journal of Electrical Power & Energy Systems, 1998
    Co-Authors: A Pandian, S A Soman, K Parthasarathy
    Abstract:

    The numerically stable power system state estimation (PSSE) algorithm uses a Givens rotations based least square (LS) solver. Row and column ordering techniques are used to reduce computations as well fills arising during sparse matrix QR decomposition. Row oriented algorithm is popularly used for QR decomposition in PSSE application with a priori Row and column ordering to reduce fills. This paper proposes online variable Pivot Row and column ordering techniques for sparse QR decomposition, which locally reduce fills during each rotation operation. Use of online ordering techniques requires a shift from Row oriented QR decomposition to column oriented QR decomposition. Simulation results on large power systems demonstrate the benefits of the proposed approach in comparison to Row oriented QR decomposition.