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Enhancements to the Cumulant Method for Probabilistic Optimal Power Flow Studies

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3 Author(s)
Ali Tamtum ; Univ. of Calgary, Calgary, AB, Canada ; Antony Schellenberg ; William D. Rosehart

This paper introduces two extenstions to the cumulant method (CM) for probabilistic optimal power flow (P-OPF) studies; the first is an enhancement to provide improved handling of limits within the P-OPF problems and the second is a way to include correlated variables. The first enhancement is termed the Limit corrected cumulant method (LCCM) which specifically addresses errors in the existing CM when limits, away from the mean solution, are encountered while solving a P-OPF problem. The LCCM approach relies on the CM to produce multiple probability density functions (PDFs) and then combines these PDFs together to generate final PDFs. The second enhancement for incorporating correlated variables into P-OPF problems is based on the composition of correlated variables from several independent ones. The proposed approaches are verified against Monte Carlo simulations (MCS) consisting of 10 000 samples and demonstrate significant improvements when compared with traditional CM results.

Published in:

IEEE Transactions on Power Systems  (Volume:24 ,  Issue: 4 )