Modeling and Numerical Analysis of Stochastic Optimal Transmission Switching with DCOPF and ACOPF

Tian Lan, Zhangxin Zhou, Garng Morton Huang

Research output: Contribution to journalArticle

Abstract

Optimal transmission switching is proposed in recent years to optimize the power system operational cost. However, grid uncertainties are not included in the previous deterministic studies. With the rapid growth of renewable generations, the uncertainties in the grid have greatly increased, which cannot be ignored when making decisions in power system operations. This paper presents two mathematical formulations for stochastic optimal transmission switching with the direct current optimal power flow (DCOPF) and the alternating current optimal power flow (ACOPF). The two stochastic formulations are analyzed and compared with the previous deterministic formulation. The ACOPF based stochastic optimal transmission switching is solved directly, while the DCOPF based stochastic optimal transmission switching is solved by the L-shaped algorithm based on the Benders decomposition. A comparative numerical study is conducted on the modified IEEE-118 bus system. In most cases, the ACOPF based stochastic optimal transmission switching achieves the lowest expected operational cost among the three methods and is faster than the DCOPF based stochastic method.

Original languageEnglish
Pages (from-to)126-131
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number28
DOIs
Publication statusPublished - 1 Jan 2018

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Numerical analysis
Costs
Decision making
Decomposition
Uncertainty

Keywords

  • optimal transmission switching
  • optimization
  • power systems
  • smart grid
  • stochastic programming

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Modeling and Numerical Analysis of Stochastic Optimal Transmission Switching with DCOPF and ACOPF. / Lan, Tian; Zhou, Zhangxin; Huang, Garng Morton.

In: IFAC-PapersOnLine, Vol. 51, No. 28, 01.01.2018, p. 126-131.

Research output: Contribution to journalArticle

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