Abstract
The purpose of this study was to provide a tool to detect NTLs and subsequently, discuss the establishment of a prepaid system in Cameroon. The conception of a prepayment system for electric power or other utility commodity distribution using Wi-Fi and GSM to store and transfer value (money or KWh, meters reading indexes) from the client module to cut-off module then to platform of the system and deliver power to the customer from the power distribution system. This system is also used as fraud detection model for the Cameroon National Electricity Company.
Highlights
Non-Technical Losses (NTLs) of energy in an electricity distribution system result from unregistered energy consumption
Knowledge on electricity consumers is important, as it provides an understanding of their consumption behaviour
Because it makes it possible to do remote metering, the management of the flows of consumption, the control of the consumptions and increase of the invoicing rate of the company in charge of the distribution and a huge gain in terms of energy to 10% of the total production of Cameroon in 2020 is 300 MW. This result is obtained on the combining of the work of this research with those carried out in our previous works on the Evaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector Machine published in American Journal of Engineering and Applied Sciences in 2017
Summary
Non-Technical Losses (NTLs) of energy in an electricity distribution system result from unregistered energy consumption These losses result from energy theft or counting and profiling errors. Knowledge on electricity consumers is important, as it provides an understanding of their consumption behaviour. With this knowledge, electricity suppliers can develop a new business strategy and offer services based on customer demand. The information that exists in the IT platform is often too complex to allow the human mind to make strategic and effective decisions or draw effective conclusions This information is often inaccessible and takes a long time to retrieve, because of the problems associated with data archived in complex database systems
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