  Agent-based solutions lend themselves well to address privacy concerns and
the computational scalability needs of future distributed electric grids and
end-use energy exchanges. Decentralized decision-making methods are the key to
enabling peer-to-peer energy trading between electricity prosumers. However,
the performance of existing decentralized decision-making algorithms highly
depends on the algorithmic design and hyperparameter tunings, limiting
applicability. This paper aims to address this gap by proposing a decentralized
inexact projection method that does not rely on parameter tuning or central
coordination to achieve the optimal solution for Peer-to-Peer (P2P) energy
trading problems. The proposed algorithm does not require parameter
readjustments, and once tuned, it converges for a wide range of P2P setups.
Moreover, each prosumer only needs to share limited information (i.e., updated
coupled variable) with neighboring prosumers. The IEEE 13 bus test system is
used to showcase our proposed method's robustness and privacy advantages.
