Open AccessSmart Grid Risk Warning Based on Multi-Level Fuzzy Analytic Hierarchy Process
Author(s) -
Liang Zhang,
Shudong Wang,
Jia guangyao,
Lu Chen
Publication year - 2019
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 - 10.1088/1742-6596/1325/1/012215
Subject(s) - smart grid , analytic hierarchy process , computer science , warning system , fuzzy logic , hierarchy , grid , reliability engineering , process (computing) , data mining , function (biology) , fuzzy set , risk analysis (engineering) , operations research , industrial engineering , engineering , artificial intelligence , mathematics , telecommunications , medicine , geometry , evolutionary biology , economics , electrical engineering , market economy , biology , operating system
Real-time control of the risks that may occur in the smart grid is of great significance for the safe and efficient operation of the smart grid. This paper establishes a risk early warning system for smart grids based on analytic hierarchy process and fuzzy theory. Firstly, the analytic hierarchy process is used to comprehensively consider the system line, load, system power supply capacity and environment and other factors to establish a smart grid evaluation index system. Then the comprehensive weights of each level of indicators are calculated, and then the evaluation matrix of the index is established by combining the membership function. Finally, the fuzzy theory is used to predict the system risk. The case study shows that the qualitative and quantitative early warning system for assessing smart grid risk has good practicability.