Name
Abstract | ||
|---|---|---|
In the study of power grid security, the cascading failure analysis in multi-contingency scenarios has been a challenge due to its topological complexity and computational cost. Both network analyses and load ranking methods have their own limitations. In this paper, based on self-organizing map (SOM), we propose an integrated approach combining spatial feature (distance)-based clustering with electrical characteristics (load) to assess the vulnerability and cascading effect of multiple component sets in the power grid. Using the clustering result from SOM, we choose sets of heavy-loaded initial victims to perform attack schemes and evaluate the subsequent cascading effect of their failures, and this SOM-based approach effectively identifies the more vulnerable sets of substations than those from the traditional load ranking and other clustering methods. As a result, this new approach provides an efficient and reliable technique to study the power system failure behavior in cascading effect of critical component failure. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TIFS.2013.2249065 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
feature clustering,pattern clustering,computational cost,critical component failure,som,power system security,power system failure behavior,attack scheme,self-organizing map,clustering method,multicontingency cascading failure analysis,load ranking method,power system reliability,substation protection,substations,power engineering computing,smart power grids,network analysis method,smart grid,attack,self-organising feature maps,topological complexity,failure cascading,electrical characteristics,power grid security,distance-based clustering,lattices,computational modeling,power system protection,self organizing map | Data mining,Smart grid,Ranking,Computer science,Electric power system,Self-organizing map,Cascading failure,Power-system protection,Cluster analysis,Topological complexity | Journal |
Volume | Issue | ISSN |
8 | 4 | 1556-6013 |
Citations | PageRank | References |
21 | 1.06 | 23 |
Authors | ||
4 | ||