Peer-to-Peer Energy Trading for PV Prosumers using Fuzzy Logic Inference Systems

This paper presents a novel method using fuzzy inference systems (FIS) to help prosumers in Florida choose between a peer-to-peer (P2P) energy network and the traditional grid. With recent changes to net metering rules, it is less profitable for prosumers to always connect to the grid. The proposed method simplifies the FIS rules by breaking up the knowledge base into three separate systems: producer, consumer, and combined prosumer. This allows for more accurate modeling of the prosumer's trading profile and maximizing profit while considering cost, reliability, and environmental impact. The simulation results show the FIS solution's ability to maximize profit compared to solely connecting to the P2P market or the grid. This work provides a valuable contribution to the literature by considering recent policy changes and discussing potential solutions for recouping losses from roof-top solar owners in Florida.