Publications

Authors:

Agostinelli, Sofia; Cumo, Fabrizio; Guidi, Giambattista; Tomazzoli, Claudio

Title:

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

Year:

2021

Type of item:

Articolo in Rivista

Tipologia ANVUR:

Articolo su rivista

Language:

Inglese

Format:

Elettronico

Referee:

Sì

Name of journal:

ENERGIES

ISSN of journal:

1996-1073

N° Volume:

14

Number or Folder:

8

Page numbers:

1-25

Keyword:

digital construction; artificial intelligence; digital twin; nZEB; energy management; energy efficiency; edge computing

Short description of contents:

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.

Product ID:

120831

Handle IRIS:

11562/1042381

Last Modified:

November 15, 2022

Bibliographic citation:

Agostinelli, Sofia; Cumo, Fabrizio; Guidi, Giambattista; Tomazzoli, Claudio, Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence «ENERGIES» , vol. 14 , n. 8 , 2021 , pp. 1-25

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