http://iet.metastore.ingenta.com
1887

PMU-based wide-area security assessment

PMU-based wide-area security assessment

For access to this article, please select a purchase option:

Buy chapter PDF
£10.00
(plus tax if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Synchronized Phasor Measurements for Smart Grids — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This chapter discusses data-mining-based catastrophe predictors using PMU-based WASI features. The study validates the performance of the black-box models such as SVM and RF through semitransparent data-mining models such as DT and transparent models such as DT_Fuzzy. It is observed from the extensive studies of the developed data-mining-based catastrophe predictors that while switching from the black box solutions to transparent and interpretable solutions, there is an unavoidable trade-off between accuracy, reliability, and security measures. The more transparent the predictor, the easier the implementation and maintenance by human actors. Overall, the fuzzy logic-based transparent solutions are preferred over black-box solutions to ease the implementation with improved robustness and enhance their suitability for auditing process, even sacrificing the predictive performance indices.

Chapter Contents:

  • 11.1 Introduction
  • 11.2 System studied using wide area monitoring
  • 11.3 Wide-area severity indices
  • 11.3.1 WASI features
  • 11.3.2 Wide-area severity indices and stability condition
  • 11.4 Data-mining models
  • 11.4.1 Decision tree
  • 11.4.2 DT-induced fuzzy approach
  • 11.4.3 Ensemble decision trees
  • 11.5 Data-mining model-based catastrophe predictors
  • 11.5.1 Scenarios and data count generation
  • 11.5.2 Data-mining models for catastrophe predictor
  • 11.5.3 Performance assessment
  • 11.5.3.1 Decision tree
  • 11.5.3.2 Ensemble decision trees (random forests)
  • 11.5.3.3 DT_Fuzzy
  • 11.5.4 Accuracy vs transparency trade off
  • 11.6 Conclusion
  • References

Inspec keywords: phasor measurement; power system security; data mining; fuzzy logic; power engineering computing

Other keywords: semitransparent data-mining model; SVM; black-box model; fuzzy logic-based transparent model; PMU-based wide-area security assessment; RF; PMU-based WASI feature; phasor measurement unit; data-mining-based catastrophe predictor

Subjects: Power engineering computing; Power system protection; Power system measurement and metering; Knowledge engineering techniques

Preview this chapter:
Zoom in
Zoomout

PMU-based wide-area security assessment, Page 1 of 2

| /docserver/preview/fulltext/books/po/pbpo097e/PBPO097E_ch11-1.gif /docserver/preview/fulltext/books/po/pbpo097e/PBPO097E_ch11-2.gif

Related content

content/books/10.1049/pbpo097e_ch11
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address