The building sector is experiencing a growing adoption of automation and control systems, Information and Communication Technologies (ICT), and IoT technologies. This trend is leading to an unprecedented availability of long-term monitoring data related to energy performance and indoor environmental quality. It is also giving rise to new approaches to energy management which also make use of digital twins. Smart technologies, including advanced metering systems, automated controls, and demand side management capabilities, enable buildings to interact with users and electrical grid in an intelligent and efficient manner. Within this context, data analytics technologies can be employed to optimize energy usage, reduce costs, manage storage and renewable technologies, and respond to grid signals, occupant needs, and environmental factors during building operation.
The research activity on data analytics-based Energy Management Systems is pushing towards the development and implementation of novel data-driven services in buildings including: the automatic detection and diagnosis of anomalous energy patterns and faults in energy systems, the implementation of predictive and adaptive control strategies in integrated energy systems, the adoption of distributed/coordinated management strategies to exploit energy flexibility at both single building and district scale (e.g., renewable energy communities).
Supervisor:
Alfonso Capozzoli www.baeda.polito.it