Power quality classification using statistical approach / Mohamad Fairuz Hassan
This paper presents a power disturbance classification using statistical method simple clustering technique that is cluster data and a conventional partitioning method that is K-Means clustering. The key idea is to compare the clustered data between these two techniques. These two approaches have th...
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| 格式: | Thesis |
| 語言: | English |
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2008
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my-uitm-ir.785742023-07-27T07:03:11Z Power quality classification using statistical approach / Mohamad Fairuz Hassan 2008 Hassan, Mohamad Fairuz Electric power distribution. Electric power transmission This paper presents a power disturbance classification using statistical method simple clustering technique that is cluster data and a conventional partitioning method that is K-Means clustering. The key idea is to compare the clustered data between these two techniques. These two approaches have the same objectives i.e. to recognize similarities, clusters and classify the disturbance to one of the identified categories. The proposed method has the potential to evaluate various power quality disturbances, such as sag, swell and notches. It also evaluates the performance of each method and discusses the strength and weaknesses of both approaches based on the simulated results. 2008 Thesis https://ir.uitm.edu.my/id/eprint/78574/ https://ir.uitm.edu.my/id/eprint/78574/2/78574.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Zakaria, Zuhaina |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| advisor |
Zakaria, Zuhaina |
| topic |
Electric power distribution Electric power transmission |
| spellingShingle |
Electric power distribution Electric power transmission Hassan, Mohamad Fairuz Power quality classification using statistical approach / Mohamad Fairuz Hassan |
| description |
This paper presents a power disturbance classification using statistical method simple clustering technique that is cluster data and a conventional partitioning method that is K-Means clustering. The key idea is to compare the clustered data between these two techniques. These two approaches have the same objectives i.e. to recognize similarities, clusters and classify the disturbance to one of the identified categories. The proposed method has the potential to evaluate various power quality disturbances, such as sag, swell and notches. It also evaluates the performance of each method and discusses the strength and weaknesses of both approaches based on the simulated results. |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Hassan, Mohamad Fairuz |
| author_facet |
Hassan, Mohamad Fairuz |
| author_sort |
Hassan, Mohamad Fairuz |
| title |
Power quality classification using statistical approach / Mohamad Fairuz Hassan |
| title_short |
Power quality classification using statistical approach / Mohamad Fairuz Hassan |
| title_full |
Power quality classification using statistical approach / Mohamad Fairuz Hassan |
| title_fullStr |
Power quality classification using statistical approach / Mohamad Fairuz Hassan |
| title_full_unstemmed |
Power quality classification using statistical approach / Mohamad Fairuz Hassan |
| title_sort |
power quality classification using statistical approach / mohamad fairuz hassan |
| granting_institution |
Universiti Teknologi MARA (UiTM) |
| granting_department |
Faculty of Electrical Engineering |
| publishDate |
2008 |
| url |
https://ir.uitm.edu.my/id/eprint/78574/2/78574.pdf |
| _version_ |
1783736258370994176 |