Neural Computing and Applications

, Volume 23, Issue 3–4, pp 645–655 | Cite as

Analysis of electricity bills using visual continuous maps

  • A. Morán
  • J. J. Fuertes
  • M. Domínguez
  • M. A. Prada
  • S. Alonso
  • P. Barrientos
New applications of Artificial Neural Networks in Modeling & Control


The information from the electricity bills of an institution such as the University of León, with several billing points, constitutes a high-dimensional data set which is quite complicated to visualize at a glance. The use of techniques for dimensionality reduction enables to obtain a two-dimensional representation of the original data set which highlights main features in data and is easier to visualize. If these techniques are combined with interpolation methods, the resulting continuous maps allow comparison and interpretation of a whole range of possible electric data sets, not only the original one. These tools allow us to generate interactive maps that can be used by untrained people to exploit and analyze the information in electricity bills, detect penalties due to a power demand excess or power factor decrease, and make decisions with regard to electricity contracts.


Dimensionality reduction Neural networks Electricity consumption Data visualization 



A. Morán was supported by a grant from the Consejería de Educación de la Junta de Castilla y León and the European Social Fund. This work was supported in part by the Spanish Ministerio de Ciencia e Innovación (MICINN) and the European FEDER funds under grant DPI2009-13398-C02-02.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • A. Morán
    • 1
  • J. J. Fuertes
    • 1
  • M. Domínguez
    • 1
  • M. A. Prada
    • 1
  • S. Alonso
    • 1
  • P. Barrientos
    • 1
  1. 1.Grupo de Investigación SUPPRESS, Instituto de Automática y Fabricación, Escuela de IngenieríasUniversidad de LeónLeónSpain

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