| dc.description.abstract | In this research, an adaptive method for illegal power connection detection and correction in domestic
distribution is presented. The focus is on a domestic supply at the meter box. Illegal power connection has been a major
challenge for many years in Kenyan power distribution network. The utility company has estimated to have lost billion
dollars yearly due to illegal power connection. The company has been trying to monitor and detect illegal power connection
especially on domestic supplies, however the methods used do not satisfactorily identify major cases of these connections.
Socio-economic aspects are the major cause that drives the power users to indulge in illegal power usage. Due to this a
cost-effective technology need to be developed not limiting to political, economic and engineering aspects to find a lasting
solution that involves all power consumers needs and more importantly considering the safety issues of the genuine power
users Several types of illegal power usage by consumers are committed but, in this research, illegally connected power users
who are aware of their connection status are considered. An adaptive Neural Fuzzy Inference system (ANFIS) is applied to
monitor, detect, determine and correct illegal power connection. A model hardware is implemented where several loads are
connected to the system to define legal and illegal power connection while also determining the extent to which power is lost.
The motivation of this research is to assist the utility company in Kenya to decrease the loss of revenue attributed by
non-technical losses which is mainly due to illegal power connection by domestic consumers. | en_US |
