An improved version of the Continuous Newton's method for efficiently solving the Power-Flow in Ill-conditioned systems


Abstract:

This paper tackles the efficient Power-Flow solution of ill-conditioned cases. In that sense, those methods based on the Continuous Newton's philosophy look very promising, however, these methodologies still present some issues mainly related with the computational efficiency or the robustness properties. In order to overcome these drawbacks, we suggest several modifications about the standard structure of the Continuous Newton's method. Thus, the standard Continuous Newton's paradigm is firstly modified with a frozen Jacobian scheme for reducing its computational burden; secondly, it is extended for being used with High-order Newton-like method for achieving higher convergence rate and, finally, a regularization scheme is introduced for improving its robustness features. On the basis of the suggested improvements, a Power-Flow solution paradigm is developed. As example, a novel Power-Flow solver based on the introduced solution framework and the 4th order Runge-Kutta formula is developed. The novel technique is validated in several realistic large-scale ill-conditioned systems. Results show that the suggested modifications allow to overcome the drawbacks presented by those methodologies based on the Continuous Newton's method. On the light of the results obtained it can be also claimed, that the developed solution paradigm constitutes a promising framework for developing robust and efficient Power-Flow solution techniques.

Año de publicación:

2021

Keywords:

  • High order Newton-like methods
  • Ill-conditioned power systems
  • Power-flow
  • Continuous Newton's method
  • Lavretiev's regularization

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Optimización matemática
  • Optimización matemática
  • Análisis numérico

Áreas temáticas:

  • Principios generales de matemáticas
  • Física aplicada
  • Ciencias de la computación