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Pattern Recognition of Power System Voltage Stability using Statistical and Algorithmic Methods

In recent years, power demands around the world and particularly in North America increased rapidly due to increase in customer’s demand, while the development in transmission system is rather slow. This stresses the present transmission system and voltage stability becomes an important issue in this regard. Pattern recognition in conjunction with voltage stability analysis could be an effective tool to solve this problem
In this thesis, a methodology to detect the voltage stability ahead of time is presented. Dynamic simulation software PSS/E is used to simulate voltage stable and unstable cases, these cases are used to train and test the pattern recognition algorithms. Statistical and algorithmic pattern recognition methods are used. The proposed method is tested on IEEE 39 bus system. Finally, the pattern recognition models to predict the voltage stability of the system are developed.

Identiferoai:union.ndltd.org:uno.edu/oai:scholarworks.uno.edu:td-2426
Date18 May 2012
CreatorsTogiti, Varun
PublisherScholarWorks@UNO
Source SetsUniversity of New Orleans
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceUniversity of New Orleans Theses and Dissertations

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