Probabilistic load flow evaluation with hybrid latin hypercube sampling and cholesky decomposition

H. Yu, C. Y. Chung, K. P. Wong, Heung Wing Joseph Lee, J. H. Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

392 Citations (Scopus)


Monte Carlo simulation method combined with simple random sampling (SRS) suffers from long computation time and heavy computer storage requirement when used in probabilistic load flow (PLF) evaluation and other power system probabilistic analyses. This paper proposes the use of an efficient sampling method, Latin hypercube sampling (LHS) combined with Cholesky decomposition method (LHS-CD), into Monte Carlo simulation for solving the PLF problems. The LHS-CD sampling method is investigated using IEEE 14-bus and 118-bus systems. The method is compared with SRS and LHS only with random permutation (LHS-RP). LHS-CD is found to be robust and flexible and has the potential to be applied in many power system probabilistic problems.
Original languageEnglish
Pages (from-to)661-667
Number of pages7
JournalIEEE Transactions on Power Systems
Issue number2
Publication statusPublished - 2 Apr 2009


  • Latin hypercube sampling
  • Monte Carlo simulation
  • Probabilistic load flow calculation
  • Uncertainty

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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