IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i8p2338-d539867.html
   My bibliography  Save this article

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

Author

Listed:
  • Sofia Agostinelli

    (CITERA Interdepartmental Centre, Sapienza University of Rome, 00197 Rome, Italy)

  • Fabrizio Cumo

    (CITERA Interdepartmental Centre, Sapienza University of Rome, 00197 Rome, Italy)

  • Giambattista Guidi

    (National Agency for New Technologies, Energy and Sustainable Economic Development, 00123 Rome, Italy)

  • Claudio Tomazzoli

    (Computer Science Department, University of Verona, 37129 Verona, Italy)

Abstract

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2338-:d:539867
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/8/2338/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/8/2338/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Francisco Javier Montiel-Santiago & Manuel Jesús Hermoso-Orzáez & Julio Terrados-Cepeda, 2020. "Sustainability and Energy Efficiency: BIM 6D. Study of the BIM Methodology Applied to Hospital Buildings. Value of Interior Lighting and Daylight in Energy Simulation," Sustainability, MDPI, vol. 12(14), pages 1-29, July.
    2. Manfren, Massimiliano & Nastasi, Benedetto & Groppi, Daniele & Astiaso Garcia, Davide, 2020. "Open data and energy analytics - An analysis of essential information for energy system planning, design and operation," Energy, Elsevier, vol. 213(C).
    3. Massimiliano Manfren & Maurizio Sibilla & Lamberto Tronchin, 2021. "Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector," Energies, MDPI, vol. 14(3), pages 1-29, January.
    4. 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.
    5. 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.
    6. Annalisa Cocchia, 2014. "Smart and Digital City: A Systematic Literature Review," Progress in IS, in: Renata Paola Dameri & Camille Rosenthal-Sabroux (ed.), Smart City, edition 127, pages 13-43, Springer.
    7. Westermann, Paul & Deb, Chirag & Schlueter, Arno & Evins, Ralph, 2020. "Unsupervised learning of energy signatures to identify the heating system and building type using smart meter data," Applied Energy, Elsevier, vol. 264(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Majidi Nezhad, Meysam & Neshat, Mehdi & Sylaios, Georgios & Astiaso Garcia, Davide, 2024. "Marine energy digitalization digital twin's approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    2. 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).
    3. Roberta Moschetti & Shabnam Homaei & Ellika Taveres-Cachat & Steinar Grynning, 2022. "Assessing Responsive Building Envelope Designs through Robustness-Based Multi-Criteria Decision Making in Zero-Emission Buildings," Energies, MDPI, vol. 15(4), pages 1-27, February.
    4. 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).
    5. Lv, Zhihan & Cheng, Chen & Lv, Haibin, 2023. "Digital twins for secure thermal energy storage in building," Applied Energy, Elsevier, vol. 338(C).
    6. Fabrizio Cumo & Federica Giustini & Elisa Pennacchia & Carlo Romeo, 2022. "The “D2P” Approach: Digitalisation, Production and Performance in the Standardised Sustainable Deep Renovation of Buildings," Energies, MDPI, vol. 15(18), pages 1-28, September.
    7. Aleksandra Kuzior & Marek Staszek, 2021. "Energy Management in the Railway Industry: A Case Study of Rail Freight Carrier in Poland," Energies, MDPI, vol. 14(21), pages 1-21, October.
    8. Marco Pau & Panagiotis Kapsalis & Zhiyu Pan & George Korbakis & Dario Pellegrino & Antonello Monti, 2022. "MATRYCS—A Big Data Architecture for Advanced Services in the Building Domain," Energies, MDPI, vol. 15(7), pages 1-22, April.
    9. Benedetto Nastasi & Massimiliano Manfren & Michel Noussan, 2021. "Open Data and Models for Energy and Environment," Energies, MDPI, vol. 14(15), pages 1-2, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Manfren, Massimiliano & Nastasi, Benedetto & Tronchin, Lamberto & Groppi, Daniele & Garcia, Davide Astiaso, 2021. "Techno-economic analysis and energy modelling as a key enablers for smart energy services and technologies in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    2. Manfren, Massimiliano & Nastasi, Benedetto, 2023. "Interpretable data-driven building load profiles modelling for Measurement and Verification 2.0," Energy, Elsevier, vol. 283(C).
    3. Massimiliano Manfren & Karla M. Gonzalez-Carreon & Patrick A. B. James, 2024. "Interpretable Data-Driven Methods for Building Energy Modelling—A Review of Critical Connections and Gaps," Energies, MDPI, vol. 17(4), pages 1-22, February.
    4. Benedetta Grassi & Edoardo Alessio Piana & Gian Paolo Beretta & Mariagrazia Pilotelli, 2020. "Dynamic Approach to Evaluate the Effect of Reducing District Heating Temperature on Indoor Thermal Comfort," Energies, MDPI, vol. 14(1), pages 1-25, December.
    5. Manfren, Massimiliano & James, Patrick AB. & Tronchin, Lamberto, 2022. "Data-driven building energy modelling – An analysis of the potential for generalisation through interpretable machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. 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).
    7. Massimiliano Manfren & Maurizio Sibilla & Lamberto Tronchin, 2021. "Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector," Energies, MDPI, vol. 14(3), pages 1-29, January.
    8. Olga Bogdanov & Veljko Jeremiæ & Sandra Jednak & Mladen Èudanov, 2019. "Scrutinizing the Smart City Index: a multivariate statistical approach," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(2), pages 777-799.
    9. Maria Conceição da Costa Silva & Alyx Diêgo Oliveira Silva & Emilia Rahnemay Kohlman Rabbani & Luciana H. Alencar & George da Mota Passos Neto & João Pedro Couto & Rodolfo Valdes-Vasquez, 2022. "Guidelines for the Implementation of BIM for Post-Occupancy Management of Social Housing in Brazil," Energies, MDPI, vol. 15(18), pages 1-20, September.
    10. Amelio, Andrea & Giardino-Karlinger, Liliane & Valletti, Tommaso, 2020. "Exclusionary pricing in two-sided markets," International Journal of Industrial Organization, Elsevier, vol. 73(C).
    11. Anthony Simonofski & Estefanía Serral Asensio & Johannes Smedt & Monique Snoeck, 2019. "Hearing the Voice of Citizens in Smart City Design: The CitiVoice Framework," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(6), pages 665-678, December.
    12. Federico Delfino & Paola Laiolo & Federico Delfino, 2019. "Living Labs and Partnerships for Progress-How Universities can Drive the Process towards the Sustainable City," International Journal of Environmental Sciences & Natural Resources, Juniper Publishers Inc., vol. 18(2), pages 71-73, April.
    13. Benjamin Maas, 2022. "Literature Review of Mobility as a Service," Sustainability, MDPI, vol. 14(14), pages 1-28, July.
    14. Claire Daniel & Christopher Pettit, 2022. "Charting the past and possible futures of planning support systems: Results of a citation network analysis," Environment and Planning B, , vol. 49(7), pages 1875-1892, September.
    15. Teresa Santos & Raquel Deus & Jorge Rocha & José António Tenedório, 2021. "Assessing Sustainable Urban Development Trends in a Dynamic Tourist Coastal Area Using 3D Spatial Indicators," Energies, MDPI, vol. 14(16), pages 1-22, August.
    16. Lorenzo Barbieri & Roberto D’Autilia & Paola Marrone & Ilaria Montella, 2023. "Graph Representation of the 15-Minute City: A Comparison between Rome, London, and Paris," Sustainability, MDPI, vol. 15(4), pages 1-14, February.
    17. Ma, Shuaiyin & Ding, Wei & Liu, Yang & Ren, Shan & Yang, Haidong, 2022. "Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries," Applied Energy, Elsevier, vol. 326(C).
    18. Maurizio Bevilacqua & Eleonora Bottani & Filippo Emanuele Ciarapica & Francesco Costantino & Luciano Di Donato & Alessandra Ferraro & Giovanni Mazzuto & Andrea Monteriù & Giorgia Nardini & Marco Orten, 2020. "Digital Twin Reference Model Development to Prevent Operators’ Risk in Process Plants," Sustainability, MDPI, vol. 12(3), pages 1-17, February.
    19. Saveria Olga Murielle Boulanger, 2022. "The Roadmap to Smart Cities: A Bibliometric Literature Review on Smart Cities’ Trends before and after the COVID-19 Pandemic," Energies, MDPI, vol. 15(24), pages 1-19, December.
    20. Johannes Stübinger & Lucas Schneider, 2020. "Understanding Smart City—A Data-Driven Literature Review," Sustainability, MDPI, vol. 12(20), pages 1-23, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2338-:d:539867. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.