Identification of the characteristics incident to the detection of non-technical losses for two Colombian energy companies

Keywords: Non-technical Losses, MDS, Hierarchical Grouping, Benford's Law, Similarity, Decision Trees, Fraud Detection


The study of non-technical losses affecting energy trading companies has guided the researchers’ perspective on different techniques and tools that allow them to detect, and why not, to forecast such losses. In the search for a solution to the problem, the different researchers rely on variables that, in many cases, the same marketing companies, from their practical experience, have been considered as incidents in the identification of the problem. However, most of the studies carried out do not support their solutions with the fact that each trading company retains particular data in which both, technical and socio-economic characteristics recorded, are not necessarily shared in their databases. In this work, we follow up on some of the characteristics registered by two Colombian energy trading companies, which serve two different regions of the country in terms of topography and idiosyncrasy. In particular, attention is focused on two characteristics measured in both companies, which by their nature, will always be on the data of any energy trading company: Consumption in kWh, and the period, measured in months. For this purpose, Benford curves analysis, MultiDimensional Scaling (MDS), and hierarchical cluster will be implemented. Finally, it will be studied if the incidence of the variables visualized in the studies presented is reflected in the decision tree model.


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Author Biographies

Carmen Cecilia Sánchez-Zuleta, Universidad de Medellín
Received the Bs. Degree in mathematics (1998), and M.Sc. degree in Mathematics (2002) from Universidad de Antioquia, Medellín, Colombia. M.Sc. degree in Applied Statistical (2010) form Universidad de Granada, Granada España, currently he is student the Ph.D. in Mathematics and Statistics in Universidad de Granada.Her research interests include Multivariate statistics, MDS, Big data, and Data mining.currently the full time professor, at the Department of Basic science , at Universidad of Medellín.
Juan Pablo Fernandez-Gutiérrez, Universidad de Medellín
received the Bs. degree in mathematics from the National University of Colombia, Campus Medellín, Medellín, Colombia, in 2003, and the M.Sc. degree in Applied Mathematics from University EAFIT, Medellín, Colombia in 2008, currently he is student the Ph.D. in Modeling, and Scientific Computing in University of Medellín.His research interests include mathematical and numerical optimization, location theory, mixed integer programming, and data mining.currently the full time professor, at the Department of Basic science , at Universidad of Medellín. 
Carlos César Piedrahita-Escobar, Universidad de Medellín
Received the Bs. degree in mathematics from the National University of Colombia, Campus Medellín, Medellín, Colombia, in 1982, and the M.A. degree in Applied Mathematics from SUNYAB, Buffalo, U.S.A. in 1986, and a Ph.D. in Applied Mathematics from UNICAMP, Campinas, Brazil in 2002.He worked at the geophysics group of the Colombian Institute of Petroleum from 1990 to 2010, where he worked a different projects related to modeling, processing and interaction with different upstream and downstream teams. Since 2012 has worked as a full time professor at The Department of Basic Science of The Universidadd e Medellín. Also has the coordination of the research group, "Grupo de Modelación y Computación Científica", category B at Colciencias.


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