IEEE transactions on power systems, 2013-02, Vol.28 (1), p.281-288
2013
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Details
- Autor(en) / Beteiligte
- Titel
- Prediction of the Transient Stability Boundary Using the Lasso
- Ist Teil von
- IEEE transactions on power systems, 2013-02, Vol.28 (1), p.281-288
- Ort / Verlag
- New York: IEEE
- Erscheinungsjahr
- 2013
- Quelle
- IEEE Xplore
- Beschreibungen/Notizen
- This paper utilizes a class of modern machine learning methods for estimating a transient stability boundary that is viewed as a function of power system variables. The simultaneous variable selection and estimation approach is employed yielding a substantially reduced complexity transient stability boundary model. The model is easily interpretable and yet possesses a stronger prediction power than techniques known in the power engineering literature so far. The accuracy of our methods is demonstrated using a 470-bus system.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 0885-8950eISSN: 1558-0679DOI: 10.1109/TPWRS.2012.2197763Titel-ID: cdi_ieee_primary_6214585
- Format
- –
- Schlagworte
- Algorithm design and analysis, Boundaries, Complexity, Conferences, Estimating, Exposure, Lasso algorithms, Machine learning, Mathematical models, Power system stability, Prediction algorithms, shrinkage methods, Stability criteria, Transient analysis, Transient stability, transient stability boundary