Novel Approaches to Data Preprocessing For Transient Stability Assessment

While continuously searching for new transient stability assessment (TSA) algorithms based on pattern recognition in recent years, less work was focused on data preprocessing which is one of important TSA components. In general, abundance of original data would increase the complexity of TSA, result...

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Bibliographic Details
Published in2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific pp. 1 - 5
Main Authors Zhonghong Yu, Xiaoxin Zhou, Zhongxi Wu
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Computational modeling
Data preprocessing
Feature extraction
fuzzy ISODATA clustering
Pattern recognition
Power system analysis computing
Power system modeling
Power system transients
Principal component analysis
Real time systems
Stability
Transient stability Assessment
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Summary:While continuously searching for new transient stability assessment (TSA) algorithms based on pattern recognition in recent years, less work was focused on data preprocessing which is one of important TSA components. In general, abundance of original data would increase the complexity of TSA, resulting in a longtime computation. In order to improve the performance of TSA, two novel data preprocessing approaches were proposed in the paper. One is fuzzy ISODATA, and the other is the modified recursive principal component analysis. In these ways, the size of data can be obviously reduced without jeopardizing the results of TSA. Simulation of a 4933-bus state grid of China system indicates higher efficiency in comparison with the traditional TSA
ISBN:0780391144
9780780391147
ISSN:2160-8636
2160-8644
DOI:10.1109/TDC.2005.1546983