CONTROL ARCHITECTURES FOR ENERGY COMMUNITIES

In this thesis we propose different solutions to a distributed optimization problem for the efficient management of energy communities (ECs). In particular we focus on the Italian case where agents of ECs can receive a monetary incentive based on the amount of “shared energy”. In a community the renewable energy produced by members equipped with renewable energy sources (RESs) can be “shared” also with not physically connected members which can consume energy at a reduced cost due to state incentives according to specific rules. There is also the possibility to equip members with battery energy storage systems (BESSs). The model assumes that each member has none, only one or both of these renewable energy production and storage systems. Cooperative distributed optimization models are proposed and they are the basis for distributed predictive control of a network of BESSs that changes the hourly amount of shared energy consumed in the community. In this way it is possible to preserve privacy of user consumption data. By comparing each approach we analyze if there are benefits regarding the cost of energy for a community and if the cooperation among BESSs owned by the members is beneficial. We also evaluate how much the creation of energy communities allows us to reduce CO2 emissions into the atmosphere.