A Novel Family of Efficient Power-Flow Methods With High Convergence Rate Suitable for Large Realistic Power Systems

Abstract

High-order power-flow (PF) solution methods are techniques with higher convergence rate than the standard Newton-Raphson (NR). This feature normally provokes that less iterations are necessary for achieving the required convergence tolerance. This advantage enables important computational savings in realistic large-scale power systems, since some expensive computations may be avoided. This article develops and analyzes a novel family of multistep PF solution techniques. The introduced solution paradigm just involves an LU decomposition along with other cheap computations each iteration. In addition, it is proved that its convergence order is equal to the number of steps considered. A comparison with other high-order PF techniques available in the literature reveals that the introduced paradigm is more efficient when more than three steps are taken. Hence, two PF methods with fourth and fifth convergence rate are developed and validated in 12 systems under different demand conditions. Results prove that the developed PF solution methods are able to notably outperform NR and the other high-order PF solvers proposed in the literature.