A Markov Chain Based Method for Probabilistic Load Flow with Wind Power

被引：0
|
作者：
Zhu, Jin-Zhou [1 ]
Zhao, Teng [1 ]
Zhang, Yan [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai, Peoples R China
来源：
2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING | 2017年
关键词：
Convolution; Markov chain; probabilistic load flow; probability-frequency distribution function; wind power; MONTE-CARLO-SIMULATION; SYSTEM RELIABILITY; MODEL;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
On the basis of Markov chain, this paper proposes a frequency and duration method for probabilistic load flow (PLF) analysis with wind power by improving the probability-frequency distribution function (PFDF) method. With this proposed method, the probability, frequency, and duration information of random output variables in the PLF problem can be efficiently computed by convolution and addition operation of PFDFs for random input variables. A numerical test on the modified IEEE-RTS79 grid verifies the effectiveness of the proposed method.
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页数：5
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