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 resi-dential 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 de-veloped 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.

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence / Agostinelli, Sofia; Cumo, Fabrizio; Guidi, Giambattista; Tomazzoli, Claudio. - In: ENERGIES. - ISSN 1996-1073. - 14:8(2021), pp. 1-27. [10.3390/en14082338]

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

Agostinelli, Sofia
Methodology
;
Cumo, Fabrizio
Supervision
;
Tomazzoli, Claudio
Software
2021

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 resi-dential 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 de-veloped 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.
2021
digital construction; artificial intelligence; digital twin; nZEB; energy management; energy efficiency; edge computing
01 Pubblicazione su rivista::01a Articolo in rivista
Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence / Agostinelli, Sofia; Cumo, Fabrizio; Guidi, Giambattista; Tomazzoli, Claudio. - In: ENERGIES. - ISSN 1996-1073. - 14:8(2021), pp. 1-27. [10.3390/en14082338]
File allegati a questo prodotto
File Dimensione Formato  
Agostinelli_Cyber-Physical_2021.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 2.37 MB
Formato Adobe PDF
2.37 MB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1543048
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 128
  • ???jsp.display-item.citation.isi??? 97
social impact