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

Author

Listed:
  • João Fausto L. de Oliveira

    (Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife 50720-001, PE, Brazil
    These authors contributed equally to this work.)

  • Paulo S. G. de Mattos Neto

    (Centro de Informática, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil
    These authors contributed equally to this work.)

  • Hugo Valadares Siqueira

    (Graduate Program in Electrical Engineering, Federal University of Technology, Ponta Grossa 84017-220, PR, Brazil
    These authors contributed equally to this work.)

  • Domingos S. de O. Santos

    (Centro de Informática, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil
    These authors contributed equally to this work.)

  • Aranildo R. Lima

    (Independent Researcher, Vancouver, BC V5K 0A3, Canada
    These authors contributed equally to this work.)

  • Francisco Madeiro

    (Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife 50720-001, PE, Brazil
    These authors contributed equally to this work.)

  • Douglas A. P. Dantas

    (Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife 50720-001, PE, Brazil
    These authors contributed equally to this work.)

  • Mariana de Morais Cavalcanti

    (Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife 50720-001, PE, Brazil
    These authors contributed equally to this work.)

  • Alex C. Pereira

    (São Francisco Hydroelectric Company (Chesf), Recife 50761-901, PE, Brazil
    These authors contributed equally to this work.)

  • Manoel H. N. Marinho

    (Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife 50720-001, PE, Brazil
    These authors contributed equally to this work.)

Abstract

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.

Suggested Citation

  • 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 Cavalcant, 2023. "Forecasting Methods for Photovoltaic Energy in the Scenario of Battery Energy Storage Systems: A Comprehensive Review," Energies, MDPI, vol. 16(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6638-:d:1240890
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    References listed on IDEAS

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