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Neural controller for the smoothness of continuous signals: an electrical grid example

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Abstract

In this paper, the use of artificial neural networks (ANNs) is proposed to manage the local demand of different electric grid elements to smooth their aggregated consumption. The ANNs are based on the load automation of the local electric behavior, following a local strategy but affecting to the global system. In an electrical grid, there is no possibility to share information between the users because anonymity must be warranted. Therefore, a solution to the problem is elaborated with the minimum information possible without the need for communication between the users. A grid environment and behavior of different users is simulated.

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Acknowledgements

This work was partially supported by the “DEMS: Sistema Distribuido de Gestión de Energía en Redes Eléctricas Inteligentes”, funded by the Programa Estatal de Investigación Desarrollo e Innovación orientada a los retos de la sociedad of the Spanish Ministerio de Economía y Competitividad (TEC2015-66126-R).

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Authors and Affiliations

  1. E.T.S. Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, 28040, Madrid, Spain

    Eduardo Matallanas, Manuel Castillo-Cagigal & Álvaro Gutiérrez

  2. Instituto de Energía Solar, Universidad Politécnica de Madrid, 28040, Madrid, Spain

    Estefanía Caamaño-Martín

Authors
  1. Eduardo Matallanas
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  2. Manuel Castillo-Cagigal
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  3. Estefanía Caamaño-Martín
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  4. Álvaro Gutiérrez
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Correspondence to Álvaro Gutiérrez.

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Matallanas, E., Castillo-Cagigal, M., Caamaño-Martín, E. et al. Neural controller for the smoothness of continuous signals: an electrical grid example. Neural Comput & Applic 32, 5745–5760 (2020). https://doi.org/10.1007/s00521-019-04139-3

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  • DOI: https://doi.org/10.1007/s00521-019-04139-3

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