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DC Field | Value | Language |
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dc.thesis.supervisor | Caldera, H.A. (Dr.) | en_US |
dc.contributor.author | Nirmalie, T.D. | - |
dc.date.accessioned | 2013-09-24T11:33:46Z | - |
dc.date.available | 2013-09-24T11:33:46Z | - |
dc.date.issued | 2013-09-24 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/33 | - |
dc.description.abstract | Electricity theft has become a significant problem for power utilities to lose a large amount of their revenue. Many researchers have tried to find an efficient measurement for detection of electricity theft. The objective of this study is to find an approach for detection of electricity theft through the analysis of electricity usage. The main motivation of this study is to assist Ceylon Electricity Board (CEB) to reduce the fraudulent electricity consumption of their domestic customers. At present CEB conducts a manual process (raid process) to identify fraudulent customers. The proposed approach is based on the analysis of electricity consumption of the customer using data mining techniques. The proposed methodology preselects suspected customers to be inspected onsite by considering the abnormal load behavior identified on their load profile using the detection rules. The proposed method is more reliable compared to the current measures taken by CEB in order to reduce electricity theft. | en_US |
dc.language.iso | en | en_US |
dc.subject | Electricity Theft | en_US |
dc.subject | data mining techniques | en_US |
dc.subject | load profile | en_US |
dc.subject | detection rules | en_US |
dc.title | Detection of Electricity Theft through Analysis of Electricity usage | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Master of Computer Science - 2013 |
Files in This Item:
File | Description | Size | Format | |
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FinalThesis.pdf Restricted Access | 5.9 MB | Adobe PDF | View/Open Request a copy |
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