"275681" . "Numerical Stability of the Newton-Raphson Method in Load Flow Analysis"@en . "Brno" . "1"^^ . . "978-80-214-4094-4" . . . "[180847E7795B]" . "University of Technology" . "Brno, \u010Cesk\u00E1 republika" . . "This paper deals with several possible approaches, which may increase numerical stability of the Newton-Raphson (N-R) algorithm in load flow analysis. Although the N-R method represents highly straightforward approach in majority of load flow cases, for power systems with rather poor convergence it may have difficulties to obtain physical solutions. Therefore, divergence or even convergence to unreasonable results may appear using the original N-R code. Fortunately, various techniques (such as state update truncation, update factor relaxation, start point estimation, etc.) can be broadly employed to avoid such non-convergent scenarios. The aim of this paper is to find the best available stabil-ity algorithm providing reliable solutions with reduced number of iterations, lowest CPU time requirements, mini-mum computational burden and modification level of the original N-R method." . "1"^^ . "RIV/49777513:23220/10:00503532" . . . . "Load Flow Analysis; Newton-Raphson algorithm; State Update Truncation; Update Factor Relaxation; One-Shot State Variable Update"@en . . "Numerical Stability of the Newton-Raphson Method in Load Flow Analysis"@en . . . "P(2A-2TP1/051), S" . . . . . "Numerical Stability of the Newton-Raphson Method in Load Flow Analysis" . "2010-01-01+01:00"^^ . . "RIV/49777513:23220/10:00503532!RIV11-MSM-23220___" . "Numerical Stability of the Newton-Raphson Method in Load Flow Analysis" . "Veleba, Jan" . "Electric Power Engineering 2010" . . "6"^^ . . "23220" . . . "This paper deals with several possible approaches, which may increase numerical stability of the Newton-Raphson (N-R) algorithm in load flow analysis. Although the N-R method represents highly straightforward approach in majority of load flow cases, for power systems with rather poor convergence it may have difficulties to obtain physical solutions. Therefore, divergence or even convergence to unreasonable results may appear using the original N-R code. Fortunately, various techniques (such as state update truncation, update factor relaxation, start point estimation, etc.) can be broadly employed to avoid such non-convergent scenarios. The aim of this paper is to find the best available stabil-ity algorithm providing reliable solutions with reduced number of iterations, lowest CPU time requirements, mini-mum computational burden and modification level of the original N-R method."@en .