Open AccessIdentification of vulnerable lines in large power grid based on FP‐growth algorithm
Author(s) -
Jiang Shengbo,
Pan Xueli,
Xiao Yi,
Zhou Qiangming,
Li Miao,
Yang Jun
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0654
Subject(s) - cascading failure , blackout , reliability engineering , computer science , reliability (semiconductor) , grid , benchmark (surveying) , process (computing) , power grid , identification (biology) , electric power system , electric power transmission , failure mode and effects analysis , power (physics) , engineering , electrical engineering , mathematics , physics , geometry , botany , quantum mechanics , biology , geodesy , geography , operating system
The complexity of the power grid structure and its operating mode has greatly enhanced, increasing the probability of the large‐scale blackout. Identifying the vulnerable lines in the process of cascading failure plays an important role in adopting effective suppression strategy to ensure the safety and stability of the power grid. An frequent pattern (FP)‐growth algorithm‐based method of identifying vulnerable lines in large power grid is proposed in this study. Based on the model of operational reliability, the cascading failures are simulated and chains of failure are generated. This study mines the sets of failure chain to discover the frequent items in the sets and to identify the vulnerable lines in the development process of cascading failures. Also, this study analyses the risk of vulnerable lines and its impact on cascading failure. Simulation results of IEEE118‐Bus benchmark show that the proposed method can identify dangerous lines in the development process of chain fault effectively, which is important for suppressing the cascading failures and reducing the power failure probability.