DocumentCode :
2598469
Title :
Reliability evaluation algorithm of electrical power system using safety margin of current space pruning
Author :
Wan, Guan Quan
Author_Institution :
Guang Zhou Power Supply Bur., Guangzhou, China
fYear :
2009
fDate :
6-7 April 2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper introduces a kind of method for quickly calculating line current under emergency state. The safety margin index of line current is introduced. The index is used to identify the key lines affected by the tripping line and forecast the system multiple fault event. Based on above all, the reliability evaluation algorithm using state pruning based on margin of safety is proposed. The margin of safety index is applied to screening out failure events with small safety margin. It can effectively prun system failure state space and coordinate the conflict between speed and precision of event reliability analysis. The application shows that the method in this paper can not only effectively implement influence and pruning analysis of event reliability, but also reflect change relations of system reliability indices with safety margins of line currents. The critical value of safety margin in relation to the risk of cascading failure can be found out. It can provide reference to decision-making for preventing the occurrence of blackouts.
Keywords :
decision making; power system reliability; cascading failure; critical value; current space pruning; decision making; electrical power system; pruning analysis; reliability evaluation; safety margin; tripping line; Algorithm design and analysis; Decision making; Electrical safety; Failure analysis; Large-scale systems; Power system analysis computing; Power system faults; Power system protection; Power system reliability; State-space methods; algorithm; power system reliability; safety margin; state pruning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4934-7
Type :
conf
DOI :
10.1109/SUPERGEN.2009.5347973
Filename :
5347973
Link To Document :
بازگشت