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.
Highlights
The energy management of building systems and urban areas such as residential districts is assuming an increasingly relevant role in the control and assessment of urban development and refurbishment processes.Digital predictive technologies and sensor-based control systems are becoming fundamental tools [1] supporting policies to reach near-zero requirements and targets for buildings and urban districts
As a consequence of the energy efficiency improvement based on the implementation of renewable energy systems, in winter conditions, the geothermal power plant supplies every building both with heating and domestic hot water; solar collectors integrate the system, while the photovoltaic system powers the external lighting system around the perimeter of the buildings
Domestic hot water is produced through solar collectors covering 100% of the actual needs, while the geothermal power plant only works for the production of chilled water for cooling, while the photovoltaic system powers the entire lighting system of the complex
Summary
The energy management of building systems and urban areas such as residential districts is assuming an increasingly relevant role in the control and assessment of urban development and refurbishment processes.Digital predictive technologies and sensor-based control systems are becoming fundamental tools [1] supporting policies to reach near-zero requirements and targets for buildings and urban districts. The integration of information communication technologies (ICT) has an important role in the configuration of smart cities and in defining digital strategies addressing social, public health, economic, environmental, and safety issues [2] The success of such digital transformations requires the ability to meet and manage new emerging challenges [3]. The introduction of DT in construction processes addresses the improvement of decision-making focusing on well-informed and advanced real-time “what-if” scenario assessments, reducing wastes of time and resources that are typical in construction In this regard, the Newcastle University created a DT of the city dedicated to incidents and disasters responding and prevention, running simulations of incidents such as burst pipes, heavy rainfall or floods to evaluate the potential impact on communities over a 24 h period [10]. The ongoing project for the city digital twin of Atlanta creates a virtual reality (VR)-based platform (built basing on the unity interactive and data-driven crossplatform game engine) which contains a three-dimensional fully modeled city of Atlanta, reproducing the entire city into a virtual space, facilitating spatial-temporal feedbacks and interactions between the human/infrastructure systems and their virtual representations [13]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
