“…In [12] we discussed three methods of choosing the forcing terms η i . Here we will use the method proposed by Eisenstat and Walker [9].…”
Section: Power Flow Solutionmentioning
confidence: 99%
“…In previous studies Φ has already proven to be a good preconditioner [10], [12], while containing only half the non-zeros of the Jacobian matrix, thus providing benefits in computing time and memory.…”
Section: Preconditioningmentioning
confidence: 99%
“…With J 0 as preconditioner the number of GMRES iteration goes up by more than is saved by having to do only one factorization. However, for higher k-levels like ILU (12), the extra GMRES iterations needed when using J 0 cost less time than the extra factorizations needed for J i .…”
Section: Numerical Experimentsmentioning
confidence: 99%
“…It has been recognized that iterative linear solvers can offer advantages over sparse direct solvers for large power systems [10,5,3,12,29]. The question arises when iterative methods are better than direct methods for power flow problems.…”
“…In [12] we discussed three methods of choosing the forcing terms η i . Here we will use the method proposed by Eisenstat and Walker [9].…”
Section: Power Flow Solutionmentioning
confidence: 99%
“…In previous studies Φ has already proven to be a good preconditioner [10], [12], while containing only half the non-zeros of the Jacobian matrix, thus providing benefits in computing time and memory.…”
Section: Preconditioningmentioning
confidence: 99%
“…With J 0 as preconditioner the number of GMRES iteration goes up by more than is saved by having to do only one factorization. However, for higher k-levels like ILU (12), the extra GMRES iterations needed when using J 0 cost less time than the extra factorizations needed for J i .…”
Section: Numerical Experimentsmentioning
confidence: 99%
“…It has been recognized that iterative linear solvers can offer advantages over sparse direct solvers for large power systems [10,5,3,12,29]. The question arises when iterative methods are better than direct methods for power flow problems.…”
“…Power flow computations in power systems, which lead to systems of non-linear equations, are no different. In our research towards improving power flow computations we have used the inexact Newton method, where an iterative linear solver is used for the linear systems [5,6].…”
The power flow model performs the analysis of electric distribution and transmission systems. With this statement at hand, in this work we present a summary of those solvers for the power flow equations, in both algebraic and parametric version. The application of the Alternating Search Direction method to the power flow problem is also detailed. This results in a family of iterative solvers that combined with Proper Generalized Decomposition technique allows to solve the parametric version of the equations. Once the solution is computed using this strategy, analyzing the network state or solving optimization problems, with inclusion of generation in real-time, becomes a straightforward procedure since the parametric solution is available. Complementing this approach, an error strategy is implemented at each step of the iterative solver. Thus, error indicators are used as an stopping criteria controlling the accuracy of the approximation during the construction process. The application of these methods to the model IEEE 57-bus network is taken as a numerical illustration.
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