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A Review on Digital Twins and Its Application in the Modeling of Photovoltaic Installations

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  • Dorotea Dimitrova Angelova

    (Department of Applied Physic, Industrial Engineering School, University of Extremadura, Avenida de Elvas s/n, 06006 Badajoz, Spain)

  • Diego Carmona Fernández

    (Department of Electrical Engineering, Electronics and Automation, Industrial Engineering School, University of Extremadura, Avenida de Elvas s/n, 06006 Badajoz, Spain)

  • Manuel Calderón Godoy

    (Department of Electrical Engineering, Electronics and Automation, Industrial Engineering School, University of Extremadura, Avenida de Elvas s/n, 06006 Badajoz, Spain)

  • Juan Antonio Álvarez Moreno

    (Department of Electrical Engineering, Electronics and Automation, Industrial Engineering School, University of Extremadura, Avenida de Elvas s/n, 06006 Badajoz, Spain)

  • Juan Félix González González

    (Department of Applied Physic, Industrial Engineering School, University of Extremadura, Avenida de Elvas s/n, 06006 Badajoz, Spain)

Abstract

Industry 4.0 is in continuous technological growth that benefits all sectors of industry and society in general. This article reviews the Digital Twin (DT) concept and the interest of its application in photovoltaic installations. It compares how other authors use the DT approach in photovoltaic installations to improve the efficiency of the renewable energy generated and consumed, energy prediction and the reduction of the operation and maintenance costs of the photovoltaic installation. It reviews how, by providing real-time data and analysis, DTs enable more informed decision-making in the solar energy sector. The objectives of the review are to study digital twin technology and to analyse its application and implementation in PV systems.

Suggested Citation

  • Dorotea Dimitrova Angelova & Diego Carmona Fernández & Manuel Calderón Godoy & Juan Antonio Álvarez Moreno & Juan Félix González González, 2024. "A Review on Digital Twins and Its Application in the Modeling of Photovoltaic Installations," Energies, MDPI, vol. 17(5), pages 1-29, March.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:5:p:1227-:d:1350961
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    References listed on IDEAS

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    1. Eneko Artetxe & Jokin Uralde & Oscar Barambones & Isidro Calvo & Imanol Martin, 2023. "Maximum Power Point Tracker Controller for Solar Photovoltaic Based on Reinforcement Learning Agent with a Digital Twin," Mathematics, MDPI, vol. 11(9), pages 1-21, May.
    2. Lu, Qing & Lü, Shuaikang & Leng, Yajun & Zhang, Zhixin, 2020. "Optimal household energy management based on smart residential energy hub considering uncertain behaviors," Energy, Elsevier, vol. 195(C).
    3. Kofinas, P. & Doltsinis, S. & Dounis, A.I. & Vouros, G.A., 2017. "A reinforcement learning approach for MPPT control method of photovoltaic sources," Renewable Energy, Elsevier, vol. 108(C), pages 461-473.
    4. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "Integrating supply and demand-side management in renewable-based energy systems," Energy, Elsevier, vol. 232(C).
    5. Pillai, Dhanup S. & Rajasekar, N., 2018. "A comprehensive review on protection challenges and fault diagnosis in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 18-40.
    6. Tolga Yalçin & Pol Paradell Solà & Paschalia Stefanidou-Voziki & Jose Luis Domínguez-García & Tugce Demirdelen, 2023. "Exploiting Digitalization of Solar PV Plants Using Machine Learning: Digital Twin Concept for Operation," Energies, MDPI, vol. 16(13), pages 1-17, June.
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