Privacy-Preserving Fully Distributed Market Clearing for Peer-to-Peer Energy Trading

The rapid growth of distributed energy resources has led to a shift toward consumer-centered electricity markets, where peer-to-peer (P2P) energy trading plays a key role. While distributed market clearing algorithms enable scalable P2P trading, they often rely on direct information exchange between all trading partners, which raises concerns about privacy and high communication overhead. To address this, we propose a fully distributed market clearing algorithm that is updated using only information from its communication neighbors, regardless of transactions relationships. To further preserve privacy, we design an enhanced version (PF-DMCA) by incorporating a lightweight privacy mechanism based on state perturbation and channel weakening. Simulation results show that both algorithms achieve convergence to a solution with less than 0.09% deviation from the optimal social welfare. Moreover, compared to existing methods, the PF-DMCA requires 85.8% of communication times to achieve convergence, while F-DMCA requires only 50.4%, demonstrating superior communication efficiency.