Global optimal polynomial approximation for parametric problems in power systems

Yongzhi Zhou, Hao Wu, Chenghong Gu, Yonghua Song

Research output: Contribution to journalArticlepeer-review

4 Citations (SciVal)


The influence of parameters on system states for parametric problems in power systems is to be evaluated. These parameters could be renewable generation outputs, load factor, etc. Polynomial approximation has been applied to express the nonlinear relationship between system states and parameters, governed by the nonlinear and implicit equations. Usually, sampling-based methods are applied, e.g., data fitting methods and sensitivity methods, etc. However, the accuracy and stability of these methods are not guaranteed. This paper proposes an innovative method based on Galerkin method, providing global optimal approximation. Compared to traditional methods, this method enjoys high accuracy and stability. IEEE 9-bus system is used to illustrate its effectiveness, and two additional studies including a 1648-bus system are performed to show its applications to power system analysis.

Original languageEnglish
Pages (from-to)500-511
Number of pages12
JournalJournal of Modern Power Systems and Clean Energy
Issue number3
Early online date21 Dec 2018
Publication statusPublished - 1 May 2019


  • Galerkin method
  • Global approximation
  • Load flow problems
  • Optimal approximation
  • Parametric problems
  • Polynomial approximation

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology


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