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Energy Digital Twin applications: A review

Author

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  • do Amaral, J.V.S.
  • dos Santos, C.H.
  • Montevechi, J.A.B.
  • de Queiroz, A.R.

Abstract

Digital Twin-based (DT) decisions are becoming increasingly popular in several areas, and the energy industry has been exploring the advantages of this approach. By creating synchronised virtual models that mirror the physical systems' behaviour, decision-makers can make more efficient and quicker decisions. In this case, this work aims to evaluate relevant papers in this area considering their objectives, application fields, adopted techniques and tools, as well as to discuss the advantages and challenges of this approach. Though a Systematic Literature Review (SLR), the main scientific databases were explored, and relevant articles were selected for analysis based on search criteria. Some crucial findings were highlighted, including the state of the art of the theme and important discussions considering energy generation, storage, transmission, and consumption subsystems. The main methods and tools adopted by the analysed literature were also evaluated and the objectives, advantages, and limitations stood out. The results of this SLR provide valuable insights for researchers and practitioners in the field and can be used to identify gaps in the current literature and provide directions for future research. It is important to mention that this work fills a gap in the literature considering the need for theoretical studies that provide a theoretical and conceptual basis for researchers and professionals in the field of Energy DTs.

Suggested Citation

  • do Amaral, J.V.S. & dos Santos, C.H. & Montevechi, J.A.B. & de Queiroz, A.R., 2023. "Energy Digital Twin applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
  • Handle: RePEc:eee:rensus:v:188:y:2023:i:c:s1364032123007499
    DOI: 10.1016/j.rser.2023.113891
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    References listed on IDEAS

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    1. Yu, Wei & Patros, Panos & Young, Brent & Klinac, Elsa & Walmsley, Timothy Gordon, 2022. "Energy digital twin technology for industrial energy management: Classification, challenges and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    2. Carlos Henrique dos Santos & José Arnaldo Barra Montevechi & José Antônio de Queiroz & Rafael de Carvalho Miranda & Fabiano Leal, 2022. "Decision support in productive processes through DES and ABS in the Digital Twin era: a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 60(8), pages 2662-2681, April.
    3. Lavinia Chiara Tagliabue & Fulvio Re Cecconi & Sebastiano Maltese & Stefano Rinaldi & Angelo Luigi Camillo Ciribini & Alessandra Flammini, 2021. "Leveraging Digital Twin for Sustainability Assessment of an Educational Building," Sustainability, MDPI, vol. 13(2), pages 1-16, January.
    4. Georgios Falekas & Athanasios Karlis, 2021. "Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects," Energies, MDPI, vol. 14(18), pages 1-26, September.
    5. Zhao Song & Christoph M. Hackl & Abhinav Anand & Andre Thommessen & Jonas Petzschmann & Omar Kamel & Robert Braunbehrens & Anton Kaifel & Christian Roos & Stefan Hauptmann, 2023. "Digital Twins for the Future Power System: An Overview and a Future Perspective," Sustainability, MDPI, vol. 15(6), pages 1-29, March.
    6. Eirini Katsidoniotaki & Foivos Psarommatis & Malin Göteman, 2022. "Digital Twin for the Prediction of Extreme Loads on a Wave Energy Conversion System," Energies, MDPI, vol. 15(15), pages 1-24, July.
    7. Chen, Ziyue & Huang, Lizhen, 2021. "Digital twins for information-sharing in remanufacturing supply chain: A review," Energy, Elsevier, vol. 220(C).
    8. Juan R. Lopez & Jose de Jesus Camacho & Pedro Ponce & Brian MacCleery & Arturo Molina, 2022. "A Real-Time Digital Twin and Neural Net Cluster-Based Framework for Faults Identification in Power Converters of Microgrids, Self Organized Map Neural Network," Energies, MDPI, vol. 15(19), pages 1-25, October.
    9. Zhao, Guanjia & Cui, Zhipeng & Xu, Jing & Liu, Wenhao & Ma, Suxia, 2022. "Hybrid modeling-based digital twin for performance optimization with flexible operation in the direct air-cooling power unit," Energy, Elsevier, vol. 254(PC).
    10. Aghaei Chadegani, Arezoo & Salehi, Hadi & Md Yunus, Melor & Farhadi, Hadi & Fooladi, Masood & Farhadi, Maryam & Ale Ebrahim, Nader, 2013. "A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases," MPRA Paper 46898, University Library of Munich, Germany, revised 18 Mar 2013.
    11. Rafaela Bortolini & Raul Rodrigues & Hamidreza Alavi & Luisa Felix Dalla Vecchia & Núria Forcada, 2022. "Digital Twins’ Applications for Building Energy Efficiency: A Review," Energies, MDPI, vol. 15(19), pages 1-17, September.
    12. Plazas-Niño, F.A. & Ortiz-Pimiento, N.R. & Montes-Páez, E.G., 2022. "National energy system optimization modelling for decarbonization pathways analysis: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    13. Tariq, Rasikh & Torres-Aguilar, C.E. & Sheikh, Nadeem Ahmed & Ahmad, Tanveer & Xamán, J. & Bassam, A., 2022. "Data engineering for digital twining and optimization of naturally ventilated solar façade with phase changing material under global projection scenarios," Renewable Energy, Elsevier, vol. 187(C), pages 1184-1203.
    14. You, Minglei & Wang, Qian & Sun, Hongjian & Castro, Iván & Jiang, Jing, 2022. "Digital twins based day-ahead integrated energy system scheduling under load and renewable energy uncertainties," Applied Energy, Elsevier, vol. 305(C).
    15. Hyang-A Park & Gilsung Byeon & Wanbin Son & Hyung-Chul Jo & Jongyul Kim & Sungshin Kim, 2020. "Digital Twin for Operation of Microgrid: Optimal Scheduling in Virtual Space of Digital Twin," Energies, MDPI, vol. 13(20), pages 1-15, October.
    16. Timothé Gronier & William Maréchal & Christophe Geissler & Stéphane Gibout, 2022. "Usage of GAMS-Based Digital Twins and Clustering to Improve Energetic Systems Control," Energies, MDPI, vol. 16(1), pages 1-17, December.
    17. Sakdirat Kaewunruen & Jessada Sresakoolchai & Lalida Kerinnonta, 2019. "Potential Reconstruction Design of an Existing Townhouse in Washington DC for Approaching Net Zero Energy Building Goal," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    18. Johan Simonsson & Khalid Tourkey Atta & Gerald Schweiger & Wolfgang Birk, 2021. "Experiences from City-Scale Simulation of Thermal Grids," Resources, MDPI, vol. 10(2), pages 1-20, January.
    19. Eshraghi, Hadi & Rodrigo de Queiroz, Anderson & Sankarasubramanian, A. & DeCarolis, Joseph F., 2021. "Quantification of climate-induced interannual variability in residential U.S. electricity demand," Energy, Elsevier, vol. 236(C).
    20. Sofia Agostinelli & Fabrizio Cumo & Giambattista Guidi & Claudio Tomazzoli, 2021. "Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence," Energies, MDPI, vol. 14(8), pages 1-25, April.
    21. Fei Tao & Fangyuan Sui & Ang Liu & Qinglin Qi & Meng Zhang & Boyang Song & Zirong Guo & Stephen C.-Y. Lu & A. Y. C. Nee, 2019. "Digital twin-driven product design framework," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3935-3953, June.
    22. de Queiroz, Anderson Rodrigo & Faria, Victor A.D. & Lima, Luana M.M. & Lima, José W.M., 2019. "Hydropower revenues under the threat of climate change in Brazil," Renewable Energy, Elsevier, vol. 133(C), pages 873-882.
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