Probabilistic Load Flow Method Based on Nataf Transformation and Latin Hypercube Sampling

Author

Yan Chen ; Jinyu Wen ; Shijie Cheng

Author_Institution

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

Volume

4

Issue

2

fYear

2013

fDate

4/1/2013 12:00:00 AM

Firstpage

294

Lastpage

301

Abstract

This paper proposed a probabilistic load flow method that can address the correlated power sources and loads. The proposed probabilistic load flow method is based on the Nataf transformation and the Latin Hypercube Sampling. The main advantage of the proposed method is that high accurate solution can be obtained with less computation. Also, it is almost unconstrained for the probability distributions of the input random variables. Considering the uncertainties of correlated wind power, solar energy and loads, the effectiveness and the accuracy of the proposed probabilistic load flow method are verified by the comparative tests in a modified IEEE 14-bus system and a modified IEEE 118-bus system.

Keywords

Monte Carlo methods; load flow; probability; sampling methods; solar power stations; wind power plants; IEEE 118-bus system; IEEE 14-bus system; Latin hypercube sampling; Nataf transformation; probabilistic load flow method; probability distributions; solar energy; wind power; Correlation; Covariance matrix; Matrix decomposition; Probabilistic logic; Random variables; Standards; Wind farms; Correlation; Latin hypercube sampling; Monte Carlo simulation; Nataf transformation; probabilistic load flow;

fLanguage

English

Journal_Title

Sustainable Energy, IEEE Transactions on

Publisher

ieee

ISSN

1949-3029

Type

jour

DOI

10.1109/TSTE.2012.2222680

Filename

6338334