Probabilistic Transient Stability Constrained Optimal Power Flow for Power Systems with Multiple Correlated Uncertain Wind Generations

Shiwei Xia, Xiao Luo, Ka Wing Chan, Ming Zhou, Gengyin Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

53 Citations (Scopus)

Abstract

This paper proposes a novel probabilistic transient stability constrained optimal power flow (P-TSCOPF) model to simultaneously consider uncertainties and transient stability for power system preventive control. While detailed wind generator model with rotor flux magnitude and angle control strategy is used to describe the dynamic behaviors of wind generators, uncertain factors with correlations, such as probabilistic load injections, stochastic fault clearing time, and multiple correlated wind generations, are also included to form a representative P-TSCOPF model. A new GSO-PE approach, consisting of an improved group search optimization (GSO) and 2m + 1 point estimated (PE) method with Cholesky decomposition, is then designed to effectively solve this challenging P-TSCOPF problem. The proposed P-TSCOPF model and GSO-PE solution approach have been thoroughly tested on a modified New England 39-bus system with correlated uncertain wind generations. Comparative results with Monte Carlo (MC) simulations have confirmed the validity of the P-TSCOPF model and demonstrated the effectiveness of GSO-PE method.
Original languageEnglish
Article number7426859
Pages (from-to)1133-1144
Number of pages12
JournalIEEE Transactions on Sustainable Energy
Volume7
Issue number3
DOIs
Publication statusPublished - 1 Jul 2016

Keywords

  • correlated wind power
  • Improved group search optimization
  • optimal power flow
  • point estimated method
  • Probabilistic transient stability
  • uncertainties

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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