Peer-to-Peer Energy Trading for Optimal Power Management of Networked Microgrid based on Particle Swarm Optimization

The deliberation of power between small interconnected multi-Microgrid systems can increase the reliability and economic benefits of power systems. In this study, a two-level hierarchical energy management strategy is proposed based on a peer-to-peer energy trading model to efficiently manage a multi-Microgrid system operating in a grid-connected mode. In the first level, the optimal size of individual Microgrids is calculated using the particle swarm optimization approach in accordance with the best annual benefit. Accordingly, the surplus and shortage of energy are calculated and sent to the second level of energy management strategy. At the second level, Microgrids are classified as sellers or buyers based on the net power consumed, and the best energy trading is determined over several rounds. To reduce harmful gas emissions and preserve the environment, two important indicators are evaluated: the level of carbon dioxide emissions and the contribution of renewable energy resources. As compared to the conventional peer-to-grid energy trading model, the outcomes demonstrated that the peer-to-peer energy trading model may enhance annual earnings while lowering gas emissions.