Title :
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
fDate :
4/1/2013 12:00:00 AM
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;
Journal_Title :
Sustainable Energy, IEEE Transactions on
DOI :
10.1109/TSTE.2012.2222680
