DocumentCode
1847919
Title
Application of bootstrap technique in power system risk assessment
Author
Kasim, S.R. ; Othman, M.M. ; Ghani, N.F.A. ; Musirin, I.
Author_Institution
Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear
2010
fDate
23-24 June 2010
Firstpage
82
Lastpage
88
Abstract
This paper presents the risk assessment of power system that takes into account the system failure indices and uncertainty of unavailable load variations estimated by using the bootstrap technique. The risk of the system is measured by using the expected energy not supplied (EENS) index as well as the probability of load curtailment (PLC). The bootstrap technique is a tool which provides simplest way to perform risk assessment of a power system. Furthermore, it also requires very little assumptions to carry-out the risk analysis and it is imperative for a small size of available information. The application of bootstrap technique is important to assess the risk indices at every level of system uncertainty. The IEEE 24-bus Reliability Test System (RTS) is used as a case study in the analysis of system risk severity based EENS and PLC. Comparative studies have been made on the risk assessment of the power system determined by using the bootstrap technique and fuzzy set.
Keywords
bootstrap circuits; power system faults; power system management; power system reliability; risk management; bootstrap technique; expected energy not supplied index; power system risk assessment; probability of load curtailment; system failure indices; unavailable load variations; Distribution functions; Equations; Mathematical model; Power transmission lines; Risk management; Uncertainty; Bootstrap technique; expected energy not supplied; probability of load curtailment; risk assessment;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering and Optimization Conference (PEOCO), 2010 4th International
Conference_Location
Shah Alam
Print_ISBN
978-1-4244-7127-0
Type
conf
DOI
10.1109/PEOCO.2010.5559246
Filename
5559246
Link To Document