Electricity theft prediction on low voltage distribution system using autoregressive technique
Electricity consumers tend to avoid the payment of electricity dues through various methods such as tampering with energy meter and illegal tapping via direct connection to the distribution feeder. This has led to huge revenue losses by the electricity supplying corporation and the related governmen...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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International Journal of Research in Engineering and Technology (IJRET)
2012
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| Online Access: | http://irep.iium.edu.my/36049/1/MY_PUBLICATIONS_IJRET015053_DEC_23_2013.pdf |
| _version_ | 1796878689345994752 |
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| author | Abdullateef, Ahmad Isqeel Salami, Momoh Jimoh Eyiomika Musse, Mohamud Ahmed Aibinu, Abiodun Musa Onasanya, Mobolaji Agbolade |
| author_facet | Abdullateef, Ahmad Isqeel Salami, Momoh Jimoh Eyiomika Musse, Mohamud Ahmed Aibinu, Abiodun Musa Onasanya, Mobolaji Agbolade |
| author_sort | Abdullateef, Ahmad Isqeel |
| collection | IIUM |
| description | Electricity consumers tend to avoid the payment of electricity dues through various methods such as tampering with energy meter and illegal tapping via direct connection to the distribution feeder. This has led to huge revenue losses by the electricity supplying corporation and the related government or private agencies. A new approach of detecting electricity theft on low voltage distribution systems, either single or three phase, based on the advanced signal processing using linear prediction is presented in this paper. Consumer data were analyzed using Autoregressive (AR) model in order to predict the quantity of power consumed within the specified interval and consequently, compare the result obtained with the actual data recorded against the consumer under study. Thus the model developed was used to predict power consumption at 30minutes interval ahead, thereby facilitating the detection of electricity theft if there is a wide variation between the actual and the predicted data.
Keywords— autoregressive model, electricity theft, linear prediction, low voltage distribution system. |
| first_indexed | 2024-03-05T23:25:06Z |
| format | Article |
| id | oai:generic.eprints.org:36049 |
| institution | International Islamic University Malaysia |
| language | English |
| last_indexed | 2024-03-05T23:25:06Z |
| publishDate | 2012 |
| publisher | International Journal of Research in Engineering and Technology (IJRET) |
| record_format | dspace |
| spelling | oai:generic.eprints.org:360492015-11-05T02:10:30Z http://irep.iium.edu.my/36049/ Electricity theft prediction on low voltage distribution system using autoregressive technique Abdullateef, Ahmad Isqeel Salami, Momoh Jimoh Eyiomika Musse, Mohamud Ahmed Aibinu, Abiodun Musa Onasanya, Mobolaji Agbolade TK5101 Telecommunication. Including telegraphy, radio, radar, television Electricity consumers tend to avoid the payment of electricity dues through various methods such as tampering with energy meter and illegal tapping via direct connection to the distribution feeder. This has led to huge revenue losses by the electricity supplying corporation and the related government or private agencies. A new approach of detecting electricity theft on low voltage distribution systems, either single or three phase, based on the advanced signal processing using linear prediction is presented in this paper. Consumer data were analyzed using Autoregressive (AR) model in order to predict the quantity of power consumed within the specified interval and consequently, compare the result obtained with the actual data recorded against the consumer under study. Thus the model developed was used to predict power consumption at 30minutes interval ahead, thereby facilitating the detection of electricity theft if there is a wide variation between the actual and the predicted data. Keywords— autoregressive model, electricity theft, linear prediction, low voltage distribution system. International Journal of Research in Engineering and Technology (IJRET) 2012 Article PeerReviewed application/pdf en http://irep.iium.edu.my/36049/1/MY_PUBLICATIONS_IJRET015053_DEC_23_2013.pdf Abdullateef, Ahmad Isqeel and Salami, Momoh Jimoh Eyiomika and Musse, Mohamud Ahmed and Aibinu, Abiodun Musa and Onasanya, Mobolaji Agbolade (2012) Electricity theft prediction on low voltage distribution system using autoregressive technique. International Journal of Research in Engineering and Technology (IJRET) , 1 (5). pp. 250-254. ISSN 2277–4378 http://psrcentre.org/images/extraimages/IJRET015053.pdf |
| spellingShingle | TK5101 Telecommunication. Including telegraphy, radio, radar, television Abdullateef, Ahmad Isqeel Salami, Momoh Jimoh Eyiomika Musse, Mohamud Ahmed Aibinu, Abiodun Musa Onasanya, Mobolaji Agbolade Electricity theft prediction on low voltage distribution system using autoregressive technique |
| title | Electricity theft prediction on low voltage distribution system using autoregressive technique |
| title_full | Electricity theft prediction on low voltage distribution system using autoregressive technique |
| title_fullStr | Electricity theft prediction on low voltage distribution system using autoregressive technique |
| title_full_unstemmed | Electricity theft prediction on low voltage distribution system using autoregressive technique |
| title_short | Electricity theft prediction on low voltage distribution system using autoregressive technique |
| title_sort | electricity theft prediction on low voltage distribution system using autoregressive technique |
| topic | TK5101 Telecommunication. Including telegraphy, radio, radar, television |
| url | http://irep.iium.edu.my/36049/1/MY_PUBLICATIONS_IJRET015053_DEC_23_2013.pdf |
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