DocumentCode
2604258
Title
Analyzing security assessment schemes in traditional networks
Author
Brooks, James ; Dunn, Rod
Author_Institution
Electr. & Electron. Eng., Univ. of Bath, Bath, UK
fYear
2009
fDate
6-7 April 2009
Firstpage
1
Lastpage
6
Abstract
The introduction of sustainable and renewable energy sources into traditional networks will be limited if we continue to use inappropriate methods for security analysis. The probabilistic nature of variable and non-schedulable renewable generation is not well represented in current on-line security assessment schemes. This paper presents a novel method of analyzing and comparing system security schemes and provides initial results of one such scheme. It does so by dynamic simulation of Monte Carlo samples on the IEEE Reliability Test System (IEEE-RTS). It aims to provide information on both how often and how badly the system security scheme fails. After testing on the IEEE-RTS it can be shown that there are credible failures that N-1 does not consider. It highlights the need for a new security assessment scheme that goes beyond a small deterministic set of test cases.
Keywords
Monte Carlo methods; power system security; renewable energy sources; IEEE Reliability Test System; Monte Carlo samples; nonschedulable renewable generation; online security assessment schemes; renewable energy sources; traditional networks; Data security; Information security; National security; Power engineering and energy; Power generation; Power system reliability; Power system security; Renewable energy resources; System testing; Wind energy generation; IEEE Reliability Test System; Power system dynamic stability; Power system reliability; Power system security; Power system simulation; Sustainable Power Generation; onte Carlo methods;
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.2009.5348262
Filename
5348262
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