Load Profiling Method in Detecting non-Technical Loss Activities in a Power Utility

This paper presents comprehensive review on nontechnical losses, load profiles and data mining techniques that currently being used in effort to minimize the non-technical loss activities. It also presents on the contributing factors in load profiles of electricity customers, using the knowledge discovery in databases (KDD) procedure, to determine the load profiles for different types of customers. In this paper, the customer load profiles are compared based on the type of day, by analysing their differences in their consumption behaviour. The objective of this study is to use the load profiling methods and data mining techniques to classify, detect and predict non-technical losses in the distribution sector, due to faulty metering and billing errors, as well as to gather knowledge on customer behaviour and preferences so as to gain a competitive advantage in the electricity market. This paper focuses mainly on the development of framework analysis of the customer behaviour.