Identification of the characteristics incident to the detection of non-technical losses for two Colombian energy companies
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 variable...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/4267
- Acceso en línea:
- http://hdl.handle.net/11407/4267
- Palabra clave:
- Benford's Law
Cluster
Decision trees
MDS
Non-technical losses
- Rights
- License
- http://purl.org/coar/access_right/c_16ec
Summary: | 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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