Modeling of maximum demand based on the number of customers

Authors

  • Alvaro Laurencio-Pérez Universidad de Holguín
  • Olga Pérez-Maliuk Universidad de Holguín
  • Igor R. Pérez-Maliuk Empresa Eléctrica de Holguín

Keywords:

clients, maximum demand, error, modeling, artificial neural network.

Abstract

A modeling was carried out to determine the maximum demand based on the number of clients in primary distribution circuits in the Holguín province. A mathematical modeling was taken into account, using the Cuervexpert 1,3 tool, and a modeling using artificial neural networks using the Matlab R2018b software, through the nntool code. In the mathematical modeling, a polynomial curve was obtained with a standard error of 1.311 and a correlation coefficient between the input and output variables (maximum demand and number of clients, respectively) of 0,833, while the artificial neural network with the best results presents a neuron in the first and second hidden layer, both with logsig function, while the output layer was constituted by a neuron with pureline transfer function, with mean square error of 1,23·10-3 and a correlation coefficient of 0,840. Both models obtained offer satisfactory results in the modeling of the characteristic maximum demand against number of customers and be applied to circuits in locations where, among other circumstances, economic conditions do not allow the placement of measurement equipment or there are limitations regarding access to services. information. 

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Published

2022-05-31

How to Cite

Laurencio-Pérez, A., Pérez-Maliuk, O., & Pérez-Maliuk, I. R. (2022). Modeling of maximum demand based on the number of customers. Ciencia & Futuro, 12(2), 155–169. Retrieved from https://revista.ismm.edu.cu/index.php/revistacyf/article/view/2169

Issue

Section

Ciencia Universitaria

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