“The main innovative aspect of the project is the combination of Artificial Intelligence techniques with data collected by sensors and smart meters, in order to create new digital services for distribution grids. The products developed consider different data availability scenarios, making the solution flexible to address restrictions on the privacy of electricity consumption data", said Ricardo Bessa, coordinator of CPES.

INESC TEC also participated with advanced R&D consultancy and tutoring of members of the data science team at ENEIDA, the project coordinator, namely considering two use cases (developed by ENEIDA): (a) estimate of installed power and PV production level from the power measurements collected at the substation; (b) identification of nodes to connect flexible energy resources, from smart metering data of the LV grid.

INESC TEC's Smart Grids and Electric Vehicles Laboratory (SGEVL) generated real electric vehicle (EV) charging records, in order to facilitate the development of innovative methodologies (developed by ENEIDA) for detecting charging EV in distribution grids.

“The technological advances of this project help improving the monitoring capacity of LV grids (local communities) and creating the technical conditions for a greater integration of renewable-based production and electric mobility at a local level", explained Ricardo Bessa.

The applications will be integrated in the intelligent management platform of ENEIDA DeepGrid®, a low-voltage grid.

The Grid2C project is co-financed by COMPETE 2020, within the scope of the Incentives System for Research and Technological Development, involving an eligible investment of €493K, which resulted in an ERDF incentive close to €341K.

The INESC TEC researcher mentioned in this news piece is associated with INESC TEC.