Open AccessRisk Element Identification of Grid Communication System Based on Improved Bayesian Network under SG and UPIOT
Author(s) -
Yishi Yue,
Jia Xuefeng,
Cunbin Li
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/508/1/012053
Subject(s) - smart grid , computer science , the internet , bayesian network , electric power system , grid , identification (biology) , telecommunications network , distributed computing , data mining , computer network , power (physics) , engineering , electrical engineering , artificial intelligence , mathematics , world wide web , physics , geometry , botany , quantum mechanics , biology
Now, Smart Grid and Ubiquitous Power Internet of Things are booming in China. The degree of coupling between the grid and the power communication system determines the degree of development of Smart Grid and Ubiquitous Electric Internet of Things. The rapid growth of Smart Grid has resulted in the risk transfer of Smart Grid Communication Systems with many levels and a strong correlation of indicators. This paper sorts out the risk indicators and provides a three-layer risk transfer network considering equipment, environment, business and operational dimension. Moreover, the triangular fuzzy number and DS evidence theory are used to assign the Bayesian network root node probability. At last, this paper identifies the risk element of SGCS and proposes preventive measures.