Enhancements to the Cumulant Method for probabilistic load flow studies

Author

Defu Cai ; Jinfu Chen ; Dongyuan Shi ; Xianzhong Duan ; Huijie Li ; Meiqi Yao

Author_Institution

State Key Lab. of Adv. Electromagn. Eng. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China

fYear

2012

fDate

22-26 July 2012

Firstpage

1

Lastpage

8

Abstract

This paper introduces two enhancements to the Cumulant Method (CM) for probabilistic load flow studies. The first one is to handle the correlation between input random variables. This enhancement models the correlated input random variables as a function of several independent ones by Cholesky decomposition and modifies CM equations. The second one is to adopt Monte Carlo sampling techniques to calculate the cumulants of input random variable with complex distribution function. The accuracy and efficiency of the proposed approaches are verified against Monte Carlo simulation method on modified IEEE 14-bus system. The impacts of wind speed correlation on power system operation are investigated by the proposed approaches.

Keywords

Monte Carlo methods; correlation methods; higher order statistics; load flow; sampling methods; CM equations; Cholesky decomposition; Monte Carlo sampling techniques; complex distribution function; correlated input random variables; cumulant method enhancements; modified IEEE 14-bus system; power system operation; probabilistic load flow studies; wind speed correlation; Correlation; Distribution functions; Electronic countermeasures; Load flow; Matrix decomposition; Random variables; Vectors; Cholesky decomposition; Cumulant Method; Monte Carlo sampling; correlation; probabilistic load flow;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Society General Meeting, 2012 IEEE

Conference_Location

San Diego, CA

ISSN

1944-9925

Print_ISBN

978-1-4673-2727-5

Electronic_ISBN

1944-9925

Type

conf

DOI

10.1109/PESGM.2012.6343972

Filename

6343972