Digital Twins: Case Study of Energy Metaverse and Edge-Cloud Integration

The emergence of novel technologies is significantly contributing to the study of new approaches to the development of energy Cyber-Physical systems. Technologies like IoT, Big Data, Machine Learning and AI are becoming so tightly coupled to be considered as a singular technological framework. Such a framework is at the basis of the Digital Twin technology, which allows to interact with a real-world asset by referring to its digital counterpart. Being potentially applied to any kind of physical asset, the Digital Twin approach can create a synergy for a comprehensive modeling, monitoring, and forecasting of the same asset. In the energy domain, Digital Twins can facilitate the decision making by providing interactive dashboards to the stakeholders within a metaverse instance. These dashboards can support what-if analyses, forecasts on energy demand and production, and remote control of the physical assets to optimize their performance. This paper proposes a framework for developing a Cyber-Physical solution in the energy domain. The framework consists of three building blocks called Physical Asset, Data Infrastructure, and Digital Twin. The Physical Asset and the Digital Twin blocks correspond to the typical counterparts of a Cyber-Physical system, whilst the Data Infrastructure is delegated to support their synchronization and/or interaction. To assess the proposed framework, a real testbed was developed as Cyber-Physical system to implement the digital twin of a smart photovoltaic station.