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Full-Text Articles in Physical Sciences and Mathematics
Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Dr David Stirling
A method based on the successful AutoClass (Cheeseman & Stutz, 1996) and the Snob research programs (Wallace & Dowe, 1994); (Baxter & Wallace, 1996) has been chosen for our research work on harmonic classification. The method utilizes mixture models (McLachlan, 1992) as a representation of the formulated clusters. This research is principally based on the formation of such mixture models (typically based on Gaussian distributions) through a Minimum Message Length (MML) encoding scheme (Wallace & Boulton, 1968). During the formation of such mixture models the various derivative tools (algorithms) allow for the automated selection of the number of clusters and …
Power Quality Data Analysis Using Unsupervised Data Mining, Ali Asheibi, David A. Stirling, Sarath Perera, D A. Robinson
Power Quality Data Analysis Using Unsupervised Data Mining, Ali Asheibi, David A. Stirling, Sarath Perera, D A. Robinson
Dr David Stirling
The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Data mining is a process that uses a variety of data analysis tools to identify hidden patterns and relationships within large samples of data. This paper presents several data mining tools and techniques that are applicable to power quality data analysis to enable efficient reporting of disturbance indices and identify network problems through pattern recognition. This paper also presents results of data mining techniques applied …
Analyzing Harmonic Monitoring Data Using Data Mining, Ali Asheibi, David A. Stirling, Danny Sutanto
Analyzing Harmonic Monitoring Data Using Data Mining, Ali Asheibi, David A. Stirling, Danny Sutanto
Dr David Stirling
Harmonic monitoring has become an important tool for harmonic management in distribution systems. A comprehensive harmonic monitoring program has been designed and implemented on a typical electrical MV distribution system in Australia. The monitoring program involved measurements of the three-phase harmonic currents and voltages from the residential, commercial and industrial load sectors. Data over a three year period has been downloaded and available for analysis. The large amount of acquired data makes it difficult to identify operational events that impact significantly on the harmonics generated on the system. More sophisticated analysis methods are required to automatically determine which part of …