Open AccessProcess Level Fault Probability Distribution Model of Intelligent Substation Based on Tree Structure
Author(s) -
Diqiu Shen,
Kefeng Zhang,
Liang Wang,
WenXing Li,
Qiaojie Zhu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2005/1/012157
Subject(s) - fault tree analysis , probability distribution , fault (geology) , process (computing) , tree (set theory) , computer science , smart grid , reliability engineering , engineering , statistics , mathematics , electrical engineering , seismology , geology , operating system , mathematical analysis
In order to estimate the probability distribution of process level fault in Smart Substation, a tree based probability distribution model of process level fault in Smart Substation is proposed. Taking 14 years' process level fault data of Smart Substation in a regional power grid as sample data, this paper compares and analyzes various probability models. The probability distribution of process level fault scale of Smart Substation in this area is calculated by using the Boley Tanner branching process model in tree structure. The experimental results show that the model can estimate the probability distribution of process level fault size of Smart Substation well. Under the same confidence requirement, the sample data needed by the method based on the Boley Tanner model to estimate the fault probability distribution is one order of magnitude less than that directly based on the actual fault data.