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.

Conflicting rules and rules with exceptions are very common in natural language specification employed to describe the behaviour of devices operating in a real-world context. This is common exactly because those specifications are processed by humans

The paper explores the use of a “digital twin model” applied to the case study of a residential district, and organized as a three-dimensional data system able to participate to the intelligent optimization and automation of the energy management and efficiency of the building system. The case study focuses on the area called Rinascimento III in Rome, consisting of 16 eight-floor building hosting 216 apartment units with an overall percentage of self-renewable energy produced by the building complex equal to 70%. This already quite high percentage means that the building complex can be defined as a Near Zero Energy Building (NZEB), i.e. a building that has a very high energy performance, and the nearly-zero or very low amount of energy required should be covered to a very significant extent by energy from renewable sources, including energy from renewable source produced on-site or nearby.

Conflicting rules and rules with exceptions are very common in natural language specification to describe the behaviour of devices operating in a real-world context. This is common exactly because those specifications are processed by humans, and humans apply common sense and strategic reasoning about those rules. In this paper, we deal with the challenge of providing, step by step, a model of energy saving rule specification and processing methods that are used to reduce the consumptions of a system of devices. We argue that a very promising non-monotonic approach to such a problem can lie upon Defeasible Logic. Starting with rules specified at an abstract level, but compatibly with the natural aspects of such a specification (including temporal and power absorption constraints), we provide a formalism that generates the extension of a basic defeasible logic, which corresponds to turned on or off devices.