Energies (Jul 2020)

Very Short-Term Power Forecasting of High Concentrator Photovoltaic Power Facility by Implementing Artificial Neural Network

  • Yaser I. Alamin,
  • Mensah K. Anaty,
  • José Domingo Álvarez Hervás,
  • Khalid Bouziane,
  • Manuel Pérez García,
  • Reda Yaagoubi,
  • María del Mar Castilla,
  • Merouan Belkasmi,
  • Mohammed Aggour

DOI
https://doi.org/10.3390/en13133493
Journal volume & issue
Vol. 13, no. 13
p. 3493

Abstract

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Concentrator photovoltaic (CPV) is used to obtain cheaper and more stable renewable energy. Methods which predict the energy production of a power system under specific circumstances are highly important to reach the goal of using this system as a part of a bigger one or of making it integrated with the grid. In this paper, the development of a model to predict the energy of a High CPV (HCPV) system using an Artificial Neural Network (ANN) is described. This system is located at the University of Rabat. The performed experiments show a quick prediction with encouraging results for a very short-term prediction horizon, considering the small amount of data available. These conclusions are based on the processes of obtaining the ANN models and detailed discussion of the results, which have been validated using real data.

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