Optimal Management for Prosumer Resources in Energy Communities with P2P Market Considering Deviation and Previously Established Agreements

The increasing growth in prosumers and the development of energy communities and peer-to-peer (P2P) exchanges present new challenges in management methods. There are algorithms in the literature for scheduling transactions between prosumers in a day-ahead market and real-time (RT) markets to resolve deviations. Still, prosumers need tools to manage the transition from one market to another. This paper proposes a mixed integer non-linear programming (MINLP) model to optimize energy requests management in the real-time market, minimize the cost of deviations, and consider new predictions while respecting agreements reached in the day-ahead market, rescheduling the operation of the devices and determining the optimal offers to submit if it is necessary. The proposed method has been evaluated using real user data from a prosumer in Seville, Spain, who has both PV generation and a battery system. The results demonstrate significant cost savings, with the proposed method achieving more than a 60% reduction compared to the scenario where the prosumer solely relies on submitting deviations to the real-time market.