Clustering of electricity demand to generate virtual load profile / Marliah Mostakim
Recently the emerging issue in the electric industry is effective power based on Smart Grid. To operate the power effectively, the data must be applicable and accessible, thus will produce the virtual load profile (VLP). To generate VLP clustering and classification are required. The clustering of c...
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2012
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| Online Access: | https://ir.uitm.edu.my/id/eprint/84625/1/84625.pdf |
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my-uitm-ir.846252024-02-14T02:23:08Z Clustering of electricity demand to generate virtual load profile / Marliah Mostakim 2012 Mostakim, Marliah Recently the emerging issue in the electric industry is effective power based on Smart Grid. To operate the power effectively, the data must be applicable and accessible, thus will produce the virtual load profile (VLP). To generate VLP clustering and classification are required. The clustering of customers electricity demand becomes important not only to design tariff but also to identify sets of standard load profile. Electricity demand means the maximum amount of electricity is being used at some time while the load profile can refer to a number of different forms of data. Clustering is one of the methods that can be used to perform the data. Clustering represent groups of customers with the same clusters are very similar and the different clusters become very distinct. In this paper, focus is on K-means and Hierarchical for clustering electricity demand and their differences are analyzed. 2012 Thesis https://ir.uitm.edu.my/id/eprint/84625/ https://ir.uitm.edu.my/id/eprint/84625/1/84625.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Zakaria, Zuhaina |
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Universiti Teknologi MARA |
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UiTM Institutional Repository |
| language |
English |
| advisor |
Zakaria, Zuhaina |
| description |
Recently the emerging issue in the electric industry is effective power based on Smart Grid. To operate the power effectively, the data must be applicable and accessible, thus will produce the virtual load profile (VLP). To generate VLP clustering and classification are required. The clustering of customers electricity demand becomes important not only to design tariff but also to identify sets of standard load profile. Electricity demand means the maximum amount of electricity is being used at some time while the load profile can refer to a number of different forms of data. Clustering is one of the methods that can be used to perform the data. Clustering represent groups of customers with the same clusters are very similar and the different clusters become very distinct. In this paper, focus is on K-means and Hierarchical for clustering electricity demand and their differences are analyzed. |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Mostakim, Marliah |
| spellingShingle |
Mostakim, Marliah Clustering of electricity demand to generate virtual load profile / Marliah Mostakim |
| author_facet |
Mostakim, Marliah |
| author_sort |
Mostakim, Marliah |
| title |
Clustering of electricity demand to generate virtual load profile / Marliah Mostakim |
| title_short |
Clustering of electricity demand to generate virtual load profile / Marliah Mostakim |
| title_full |
Clustering of electricity demand to generate virtual load profile / Marliah Mostakim |
| title_fullStr |
Clustering of electricity demand to generate virtual load profile / Marliah Mostakim |
| title_full_unstemmed |
Clustering of electricity demand to generate virtual load profile / Marliah Mostakim |
| title_sort |
clustering of electricity demand to generate virtual load profile / marliah mostakim |
| granting_institution |
Universiti Teknologi MARA (UiTM) |
| granting_department |
Faculty of Electrical Engineering |
| publishDate |
2012 |
| url |
https://ir.uitm.edu.my/id/eprint/84625/1/84625.pdf |
| _version_ |
1794192032861782016 |