Energies (Sep 2023)

Forecasting Methods for Photovoltaic Energy in the Scenario of Battery Energy Storage Systems: A Comprehensive Review

  • João Fausto L. de Oliveira,
  • Paulo S. G. de Mattos Neto,
  • Hugo Valadares Siqueira,
  • Domingos S. de O. Santos,
  • Aranildo R. Lima,
  • Francisco Madeiro,
  • Douglas A. P. Dantas,
  • Mariana de Morais Cavalcanti,
  • Alex C. Pereira,
  • Manoel H. N. Marinho

DOI
https://doi.org/10.3390/en16186638
Journal volume & issue
Vol. 16, no. 18
p. 6638

Abstract

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The worldwide appeal has increased for the development of new technologies that allow the use of green energy. In this category, photovoltaic energy (PV) stands out, especially with regard to the presentation of forecasting methods of solar irradiance or solar power from photovoltaic generators. The development of battery energy storage systems (BESSs) has been investigated to overcome difficulties in electric grid operation, such as using energy in the peaks of load or economic dispatch. These technologies are often applied in the sense that solar irradiance is used to charge the battery. We present a review of solar forecasting methods used together with a PV-BESS. Despite the hundreds of papers investigating solar irradiation forecasting, only a few present discussions on its use on the PV-BESS set. Therefore, we evaluated 49 papers from scientific databases published over the last six years. We performed a quantitative analysis and reported important aspects found in the papers, such as the error metrics addressed, granularity, and where the data are obtained from. We also describe applications of the BESS, present a critical analysis of the current perspectives, and point out promising future research directions on forecasting approaches in conjunction with PV-BESS.

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