Title :
Search strategy for cascading failure in power systems based on genetic algorithm
Author :
Zhiyuan Ma ; Libao Shi ; Yixin Ni ; Liangzhong Yao ; Bazargan, Masoud
Author_Institution :
Nat. Key Lab. of Power Syst. in Shenzhen, Tsinghua Univ., Shenzhen, China
Abstract :
This paper presents a search strategy to identify the chains of events that may lead to cascading failures in power systems. The genetic algorithm is applied to implement the search strategy in accordance with a proposed combined risk index incorporating severity and probability of contingency information. The system frequency characteristics are taken into account as well during analysis. Finally, the case studies are conducted to demonstrate the validity of the proposed model and method.
Keywords :
genetic algorithms; power system faults; power system planning; power system reliability; cascading failure; contingency information; genetic algorithm; power system; search strategy; system frequency characteristic; Genetic algorithms; Indexes; Load flow; Power system faults; Power system protection; Search problems; GA; cascading failure; dynamic power flow; event chain; hidden failures;
Conference_Titel :
TENCON 2013 - 2013 IEEE Region 10 Conference (31194)
Conference_Location :
Xi´an
Print_ISBN :
978-1-4799-2825-5
DOI :
10.1109/TENCON.2013.6718880