Computational BIM and Intelligent Operations

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

Agostinelli Sofia, Cumo Fabrizio, Guidi Giambattista, Tomazzoli Claudio

Published 2021

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📄 Paper
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.

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.

Topics

AI building automationAI for Energy Performance OptimizationBIMPredictive Analytics and Performance OptimizationSmart Building Systems and IoT Integrationbuilding energy forecastingbuilding energy simulationbuilding performance dashboarddigital twinshuman-centric IoTpredictive analyticssensor data integration

Cite this paper

@Article{36b43448,
AUTHOR = {Agostinelli, Sofia and Cumo, Fabrizio and Guidi, Giambattista and Tomazzoli, Claudio},
TITLE = {Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence},
JOURNAL = {Energies},
VOLUME = {14},
YEAR = {2021},
NUMBER = {8},
ARTICLE-NUMBER = {2338},
URL = {https://www.mdpi.com/1996-1073/14/8/2338},
ISSN = {1996-1073},
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.},
DOI = {10.3390/en14082338}
}