Entitled "Modelling and Optimization for Green Transition of Complex Energy Networks"  Prof. Glielmo's presentation highlighted modelling and optimization tools being developed within the Ecodream project to address certain known challenges that need to be resolved in the context of promoting wider adoption of renewable energy communities across Europe. 

The future smart grid envisions a de-regularized operation of the modern-day power system with "actors" present at different levels in the hierarchy coordinating with each other, rather than having a centralized control mechanism. This shift derives from the inclusion in the mix of distributed generation, renewable energy resources, storage units, etc., leading to novel concepts like microgrids, nanogrids, and energy communities.

On the one hand, the de-regularization provides greater autonomy to the involved actors, wherein they can make decisions that maximize their arbitrage; on the other, it brings its own challenges in terms of grid resiliency and robustness given that the overall power network is physically coupled.

To address these issues in a manner that complies with the relevant European directives, a bottom up approach is utilized which is based on considering the residential households within a residential neighborhood as the actors. Borrowing tools and techniques from optimization, game theory and reinforcement learning, we address a range of problems are addressed such as component sizing for PV panels and storage units and optimal scheduling of flexible resources, such as electric vehicles and storage units. 

 Fig 1: Initiatives Towards Green Transition

Fig 2: Renewable Energy Communities