Fast voltage collapse evaluation via fuzzy decision tree method

Voltage stability is considered to be a complex field of study since it has a number of contributing factors. Due to this, numerous studies or research has been made to look into various methods of analysis, detection and mitigation. In general, these methods would involve either complex computation...

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Bibliographic Details
Published inProceedings. National Power Engineering Conference, 2003. PECon 2003 pp. 1 - 4
Main Authors Abidin, H.I.H.Z., Lo, K.L., Hussein, Z.F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Artificial intelligence
Decision trees
Fuzzy sets
Machine learning
Machine learning algorithms
Power system analysis computing
Power system stability
Stability analysis
System testing
Voltage
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Summary:Voltage stability is considered to be a complex field of study since it has a number of contributing factors. Due to this, numerous studies or research has been made to look into various methods of analysis, detection and mitigation. In general, these methods would involve either complex computation for accurate results but suffers from high computation time. Some methods may also be simple and fast but then has the disadvantage of inaccuracy. This paper presents an alternative method of analysing the voltage stability problem by incorporating machine learning techniques, i.e. fuzzy decision tree method. The author proposed a general overview on how the algorithm is created. The algorithm is then tested using an IEEE 300 bus test system to test the algorithm's capability. Results presented show that the proposed FDT has a lot of future potential as an online tool for voltage stability analysis.
ISBN:0780382080
9780780382084
DOI:10.1109/PECON.2003.1437406