subject:(Illegal electricity )

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University of KwaZulu-Natal

1. Mbanjwa, Thobile. An analysis of electricity theft : the case study of KwaXimba in eThekwini, KwaZulu-Natal.

Degree: 2017, University of KwaZulu-Natal

The illegal consumption of electricity is deemed a criminal offence that is punishable. Even so, there exist high levels of theft of electricity till date. Illegal electricity can be dangerous in nature due to the nature of its installation. These connections are done by non-expert persons and some of the safety precautions are not followed through. As a result, communities suffer the consequences. This study intended to identify the motivations behind the illegal consumption of electricity in the KwaXimba community. An investigation is also done on what are the effects of the theft of electricity on the community. This was a deliberate attempt to uncover whether communities are aware of such dangers. Eskom is aware of such and has a number of preventative measures against the theft of electricity, in place. This study aimed to investigate, the strategies in place in an attempt to curb electricity theft. This study investigated the illegal connections of electricity in KwaXimba. The main objective of the study was to determine the major cause of electricity theft in KwaXimba, the approaches implemented to reduce the rise in electricity theft moreover, it aimed to evaluate the effects electricity theft has on electricity supply and the community. In order to achieve this, the qualitative approaches were used. Interviews were conducted on participants that were purposively selected. The data was then analysed thematically. Findings of this study revealed that the issue of electricity theft in the community was a structural issue. The issue of theft is normalised within the community. The study revealed that individuals steal electricity based on personal decisions and preferences. Another factor was that it is acceptable to steal electricity in the community. The minority of the members stole electricity because they had bought houses that had readily stolen electricity. The researcher deduced some recommendations from the study, for one, an electrification program should be made to save both Eskom Revenue from illegal consumption and to save the lives of the community members especially the vulnerable group, children who fall victims to exposed cables. Also, organisations such as community safety and Eskom should formulate programs that are aimed towards de-normalising the act of electricity theft in the community of KwaXimba and across other communities. Advisors/Committee Members: Mkhize, Sazelo Michael. (advisor).

Subjects/Keywords: Electricity theft.; Illegal electricity.; Eskom revenue.; Izinyokanyoka.

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APA (6^th Edition):

Mbanjwa, T. (2017). An analysis of electricity theft : the case study of KwaXimba in eThekwini, KwaZulu-Natal. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/16105

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mbanjwa, Thobile. “An analysis of electricity theft : the case study of KwaXimba in eThekwini, KwaZulu-Natal.” 2017. Thesis, University of KwaZulu-Natal. Accessed January 23, 2021. http://hdl.handle.net/10413/16105.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mbanjwa, Thobile. “An analysis of electricity theft : the case study of KwaXimba in eThekwini, KwaZulu-Natal.” 2017. Web. 23 Jan 2021.

Vancouver:

Mbanjwa T. An analysis of electricity theft : the case study of KwaXimba in eThekwini, KwaZulu-Natal. [Internet] [Thesis]. University of KwaZulu-Natal; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10413/16105.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mbanjwa T. An analysis of electricity theft : the case study of KwaXimba in eThekwini, KwaZulu-Natal. [Thesis]. University of KwaZulu-Natal; 2017. Available from: http://hdl.handle.net/10413/16105

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Depuru, Soma Shekara. Modeling, Detection, and Prevention of Electricity Theft for Enhanced Performance and Security of Power Grid.

Degree: PhD, College of Engineering, 2012, University of Toledo

URL: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341522225

This dissertation contributes to the development and implementation of novel algorithms for analyzing the electricity consumption patterns of customers and identifying illegal consumers based on irregularities in consumption. Distribution of electricity involves significant Technical as well as Non-Technical Losses (NTL). Illegal consumption of electricity or electricity theft constitutes a major share of NTL. This dissertation discusses several methods implemented by illegal consumers for stealing electricity and provides relevant literature review. A comprehensive review of the advantages, challenges and technologies involved in the design, development, and deployment of smart meters is presented. With the advent of advanced metering technologies, real-time energy consumption data will be available at the utilities end, which can be used to detect illegal consumers. This dissertation presents an encoding technique that simplifies the received customer energy consumption readings (patterns) and maps them into corresponding irregularities in consumption. The encoding technique preserves the exclusivity in the energy consumption patterns. The encoding technique saves significant CPU time in the real-time analysis and classification of customers, in addition to decreasing the memory required to store historical data. Then, this dissertation elucidates operation of intelligent classification techniques on customer energy consumption data to classify genuine and illegal consumers. These classification models are applied on regular energy consumption data as well as the encoded data to compare corresponding classification accuracies and computational overhead. Further, performance and scope of the proposed algorithms is enhanced in two directions - reducing the overall computation time, and including more real-time parameters using High Performance Computers (HPC). The encoding and classification algorithms are parallelized (in both Task Parallel and Data Parallel approaches). On the other hand, impact of Time-Based Pricing (TBP) and Distributed Generation (DG) on illegal consumers as well as the algorithms used for detection of illegal consumers are analyzed. Economics involved in terms of losses due to illegal consumption of electricity is also explained. Advisors/Committee Members: Wang, Lingfeng (Committee Chair), Devabhaktuni, Vijay (Committee Co-Chair).

Subjects/Keywords: Electrical Engineering; Non-Technical Losses; Detection of Electricity Theft; Neural Network; SVM; Data Classification; Rule Engine; Smart Grid; Smart Meter; Power Grid; Fraud/Illegal consumption of electricity; HPC; DG

…71 Identifying Illegal Consumers of Electricity using High Performance, Intelligent… …electricity consumption to detect illegal consumers… …100 7-5: Money lost by the utility in a single day due to illegal consumption of electricity… …NTL. Major forms of electricity theft include bypassing (illegal tapping of electricity… …25 Billion every year due to illegal consumption of electricity. For example, utilities in…

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Record Details Similar Records Cite « Share

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Depuru, S. S. (2012). Modeling, Detection, and Prevention of Electricity Theft for Enhanced Performance and Security of Power Grid. (Doctoral Dissertation). University of Toledo. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341522225

Chicago Manual of Style (16^th Edition):

Depuru, Soma Shekara. “Modeling, Detection, and Prevention of Electricity Theft for Enhanced Performance and Security of Power Grid.” 2012. Doctoral Dissertation, University of Toledo. Accessed January 23, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341522225.

MLA Handbook (7^th Edition):

Depuru, Soma Shekara. “Modeling, Detection, and Prevention of Electricity Theft for Enhanced Performance and Security of Power Grid.” 2012. Web. 23 Jan 2021.

Vancouver:

Depuru SS. Modeling, Detection, and Prevention of Electricity Theft for Enhanced Performance and Security of Power Grid. [Internet] [Doctoral dissertation]. University of Toledo; 2012. [cited 2021 Jan 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341522225.

Council of Science Editors:

Depuru SS. Modeling, Detection, and Prevention of Electricity Theft for Enhanced Performance and Security of Power Grid. [Doctoral Dissertation]. University of Toledo; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341522225

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