Renewable Energy communities (RECs) can enable grid integration of decentralized renewable energy by coordinating local renewable generation, storage and flexible and unflexible loads, thereby improving local system balancing and providing flexibility to support a more efficient distribution network operation. Therefore, the large-scale deployment of RECs is seen as an additional key driver for the integration of renewable generation and power system decarbonization.

In this context, third-party business models can help to support the deployment of RECs, as external developers can finance and operate shared assets, helping overcome the upfront investment and organizational barriers faced by community members. This work develops a bilevel optimization framework for the operation of a REC composed of a promoter with distributed generation, battery storage and electric vehicles, and a set of community members acting as price-responsive consumers with prices set by the REC promoter. Those members that make their facilities available to the promoter to install PV panels to sell this generation to the REC members get a discount on the energy they self-consumed.

The problem for scheduling the promoter resources is formulated as a leader-follower structure, with the leader being the promoter and the followers the REC members. In this bilevel approach, the leader takes strategic decisions corresponding to schedule of its own assets, anticipating the optimal response of the followers, while the followers optimize their assets schedules to minimize their own costs. At the upper level, the promoter seeks to minimize the net operating cost, accounting for retail electricity procurement, battery and electric vehicle degradation, and revenues from local energy sales to community members. To ensure reasonably fair energy sharing among all REC members, a quadratic cost is added to the allocated energy in the upper-level to penalize overallocations to a single REC member.

Results show that the proposed bilevel optimization represents properly the reaction of the REC members when they own flexible assets, which is in turn considered by the promoter to take its own scheduling decisions. In addition, it yields better outcomes for all involved parties in comparison to their individual standalone costs, so that REC member sees a benefit from belonging to the REC, proving it a viable tool for analysing REC development and integration.