Typical demand curvs of electric power for the residential, commercial and industrial sector of Medellin, using artificial neural networks and algorithms of interpolation

Authors

  • Héctor Tabares Universidad de Antioquia
  • Jesús Hernández Universidad Nacional de Colombia

Keywords:

: Artificial neural networks, interpolation algorithms, electric power demand

Abstract


One of the main problems for modeling the electric power consumption in a certain place is the extraction of the knowledge when it is stored in big volumes of information like for example historical registrations. According with this representation, each fact happened and registered consists of a couple of components (t, P) where t represents the time of sample registration and P the electric power consumed at that time. The daily registration has N cases that each of the well-known stimulus-answer couples represents. The objective of this work is to develop a function that allows finding the vector of entrance variables t to the vector of exit variables P. F is any function, in this case the electric power consumption. Their modeling with Artificial Neural Netwok (ANN) is Multi a Perceptron Layer (PMC). Another form of modeling it is using Interpolation Algorithms(AI).

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Author Biography

Héctor Tabares, Universidad de Antioquia

Departamento de Ingeniería Eléctrica, Facultad de Ingeniería

References

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Facultad de Ingeniería, Universidad de Antioquia. http://jaibana.udea.edu.co/producciones/programas.html. Consultada el 4 de Marzo de 2007.

Published

2013-12-11

How to Cite

Tabares, H., & Hernández, J. (2013). Typical demand curvs of electric power for the residential, commercial and industrial sector of Medellin, using artificial neural networks and algorithms of interpolation. Revista Facultad De Ingeniería Universidad De Antioquia, (46), 110–118. Retrieved from https://revistas.udea.edu.co/index.php/ingenieria/article/view/17934