Optimal Peer-to-Peer Energy Trading Under Load Uncertainty Incorporating Carbon Emission and Transaction Cost for Grid-Connected Prosumers - Hien Thanh Doan; Heungwoo Nam; Daehee Kim (IEEE Access, 2022)
With the increasing deployment of renewable energy sources, peer-to-peer (P2P) energy trading has recently garnered considerable attention. Many studies have investigated P2P energy trading between prosumers without considering the existing main grid. However, integrating the P2P energy trading of renewable energy in microgrids into the existing systems is a key measure to meet the requirements of energy policy and complement the existing systems. Thus, we propose a decentralized P2P energy trading model to encourage and manage energy transactions among prosumers in a grid-connected microgrid network with photovoltaic systems. Each peer, as a prosumer in the network, forms relationships in which an agent only needs to communicate and negotiate with its neighbors through communication layer to reach an optimal solution for P2P trading in a decentralized manner without requiring any central authority. In our proposed P2P energy trading model, prosumers with demand response availability optimize their objectives by maximizing social welfare and minimizing costs while considering carbon emissions and transaction costs. The proposed model is completely decentralized, privacy-preserving, and scalable by effectively applying a distributed alternating direction method of multipliers. A detailed case study considering a group of eight prosumers is presented to demonstrate the performance and superiority of the proposed P2P energy-trading system. Considering the global convergence criterion, prosumers achieved a maximum total social welfare while minimizing both the energy cost from the grid and costs related to trading with other prosumers.