Jesús Biscarri

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Datamining has become increasingly common in both the public and private sectors. A non-technical loss is defined as any consumed energy or service which is not billed because of measurement equipment failure or illintentioned and fraudulent manipulation of said equipment. The detection of non-technical losses (which includes fraud detection) is a field(More)
This paper describes a method proposed in order to recover electrical energy (lost by abnormality or fraud) by means of a data mining analysis based in outliers detection. It provides a general methodology to obtain a list of abnormal users using only the general customer databases as input. The hole input information needed is taken exclusively from the(More)
This paper deals with the characterization of customers in power companies in order to detect consumption Non-Technical Losses (NTL). A new framework is presented, to find relevant knowledge about the particular characteristics of the electric power customers. The authors uses two innovative statistical estimators to weigh variability and trend of the(More)
The MIDAS project began at 2006 as collaboration between Endesa, Sadiel and the University of Seville. The objective of the MIDAS project is the detection of Non-Technical Losses (NTLs) on power utilities. The NTLs represent the non-billed energy due to faults or illegal manipulations in clients’ facilities. Initially, research lines study the application(More)
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