A new point estimate method for probabilistic load flow with correlated variables including wind farms

In this paper, a novel probabilistic load flow (PLF) method that combines Nataf transformation with Zhao's point estimate method (PEM) is proposed. The new method can deal with correlated non-normal input random variables (RVs) in PLF evaluation with improved accuracy and less computation time...

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Bibliographic Details
Published in2014 IEEE PES General Meeting | Conference & Exposition pp. 1 - 5
Main Authors Can Chen, Wenchuan Wu, Boming Zhang, Singh, Chanan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2014
Subjects
Correlation coefficient
Load flow
Load modeling
Nataf transformation
point estimate method
probabilistic load flow
Probabilistic logic
Wind farms
wind power
Wind speed
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Summary:In this paper, a novel probabilistic load flow (PLF) method that combines Nataf transformation with Zhao's point estimate method (PEM) is proposed. The new method can deal with correlated non-normal input random variables (RVs) in PLF evaluation with improved accuracy and less computation time than existing methods. The proposed method is applied to a modified IEEE 118-bus test system with wind farms. A comparison with Monte Carlo Simulation (MCS) using correlated variables is presented. In the end, the sensitivity analysis considering different correlation coefficients of wind speed is shown.
ISSN:1932-5517
DOI:10.1109/PESGM.2014.6939141