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Exact Penalty Function Based Constraint Relaxation Method for Optimal Power Flow Considering Wind Generation Uncertainty

  • Tao Ding
  • , Rui Bo
  • , Fangxing Li
  • , Yang Gu
  • , Qinglai Guo
  • , Hongbin Sun
  • Tsinghua University
  • Midwest Independent Transmission System Operator
  • University of Tennessee

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

This letter presents a constraint relaxation optimal power flow (OPF) model to tackle the issues when traditional OPF is infeasible under large variations such as wind generation output. In this model, the original hard constraints are relaxed into soft constraints and the objective function is adjusted for the cost of constraint violations. To guarantee the equivalence to the original OPF model when there are feasible solutions, an exact penalty function method is introduced to justify the selection of penalty factor of constraint violations. By solving an optimization problem, the lower bound of the proper penalty factor is obtained. The results of a 6-bus test system show that the proposed method achieves the same solution when the original OPF has feasible region, and an optimal solution can be obtained with minimum constraint violation when original OPF has no feasible region. Lastly, three large IEEE systems are tested to verify the effectiveness of proposed method.

Original languageEnglish
Article number6874597
Pages (from-to)1546-1547
Number of pages2
JournalIEEE Transactions on Power Systems
Volume30
Issue number3
DOIs
StatePublished - 1 May 2015
Externally publishedYes

Keywords

  • Bi-level programming
  • Karush-Kuhn-Tucker (KKT) conditions
  • constraint relaxation
  • exact penalty function
  • optimal power flow (OPF)
  • wind power

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