SCANERGY will be built up by an intelligent multi-agent system that can manage the electricity produced and consumed both on a lower level (dwellings and neighbourhoods) as well as on a higher level (cities). The SCANERGY system enables the smart energy trade between prosumers, while coping with the inherent real-time dynamism in electricity demand and supply.

The system will include an integration layer for the currently available energy infrastructure and will allow a near real-time coordinated control of the produced and consumed energy in dwellings, neighbourhoods and cities. The software and ICT modules will implement innovative simulation and prediction models, both online and offline, as well as optimization algorithms that will leverage a more effective and rational usage of all resources available in a city.

The project will enable a more efficient usage of renewable energy, the reduction of Greenhouse Gas Emissions (GGE), including the quantification of GGE reduction, the improvement of Indoor Air Quality (IAQ) and other comfort indicators. A high-level integrated computational management system will make use of data (independently of specific devices and configurations) and information that is available in real-time in the city’s energy management systems.

Research topics:  

• Learning in Multi-Agent Systems
• Machine Learning for Data mining