期刊
IET GENERATION TRANSMISSION & DISTRIBUTION
卷 8, 期 9, 页码 1539-1549出版社
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-gtd.2013.0649
关键词
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资金
- National Basic Research Program of China (973 Program) [2009CB219701]
- National High Technology Research and Development of China (863 Program) [2011AA05A101, 2011AA05A109]
- National Natural Science Foundation of China (NSFC) [50937002]
- Science and Technology Project of China Southern Power Grid [CSG [2013]0301ZD1]
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.
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