This paper introduces a novel iterative dynamic pricing framework designed for peer-to-peer (P2P) energy exchange within microgrids populated by photovoltaic (PV) prosumers. Addressing the volatility of renewable generation and the constraints of conventional feed-in tariff (FiT) systems, the proposed model integrates two distinct pricing algorithms: supply-to-demand ratio (SDR) and dynamic supply-to-demand ratio (DSDR) across three tariff scenarios: fixed pricing, real-time pricing (RTP), and time-of-use pricing (TOU). An iterative computational procedure is developed to achieve economic equilibrium among participants.

Quantitative analysis of prosumer costs, revenues, and net costs demonstrates significant improvements under the proposed framework. First, compared to grid-only transactions, all P2P pricing methods reduce costs and increase revenues. Cost reductions range from 8% to 15%, revenue increases range from 70% to 115%, and net cost reductions range from 10% to 25%. Among all P2P methods, the DSDR model with TOU tariffs delivers the best performance relative to grid trading, achieving the highest cost savings and revenue increases. Second, comparing the pricing methods internally, the DSDR model consistently outperforms the SDR model across all tariff scenarios. The DSDR model with TOU achieves the best overall performance, reducing net costs by 15% to 18% compared to SDR with TOU, and by 17% to 22% compared to SDR with fixed pricing. These findings confirm that while all proposed pricing methods contribute to economic improvements, the DSDR pricing method combined with TOU tariffs consistently delivers the most favorable outcomes across all prosumer categories.