Probabilistic load flow computation using Copula and Latin hypercube sampling

Author

Defu Cai ; Dongyuan Shi ; Jinfu Chen

Author_Institution

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

Volume

8

Issue

9

fYear

2014

fDate

Sept. 2014

Firstpage

1539

Lastpage

1549

Abstract

A probabilistic load flow (PLF) method using Copula and improved Latin hypercube sampling is proposed. The stochastic dependence between input random variables is considered. Copula theory is adopted to establish the probability distribution of correlated input random variables. Based on discrete data, an improved Latin hypercube sampling is proposed. The accuracy of probability distribution of correlated input random variables established by Copula theory is evaluated by adopting the power output of wind farms located at New Jersey. The performance of the proposed PLF method is investigated using IEEE 14-bus and IEEE 118-bus test systems.

Keywords

load flow; sampling methods; statistical distributions; stochastic processes; wind power plants; Copula theory; IEEE 118-bus test systems; IEEE 14-bus test systems; New Jersey; PLF method; correlated input random variables; discrete data; improved Latin hypercube sampling; probabilistic load flow computation; probability distribution; stochastic dependence; wind farms;

fLanguage

English

Journal_Title

Generation, Transmission & Distribution, IET

Publisher

iet

ISSN

1751-8687

Type

jour

DOI

10.1049/iet-gtd.2013.0649

Filename

6887469