An Optimal Multi-Path Power Routing and Transmission Scheduling Approach for Peer-to-Peer Power Trading in Energy Internet

Energy Internet exploits a network of sparsely in-terconnected prosumers and maximizes the peer-to-peer power exchanges by routing power through intermediate peers. A novel graph theory-based deterministic approach for P2P power routing that aids efficient distance-based prosumer matching while addressing limited connectivity challenges is presented here. The proposed Optimal-Walk Multi-path Power Routing (OMPR) approach consists of two steps. First, an optimal-walk connectivity algorithm calculates the shortest path between all the nodes. Leveraging this data, in the second part, the Multi-path Power Routing (MPR) algorithm, identifies optimal paths for handling multiple simultaneous P2P exchanges. In the MPR algorithm, the power scheduling and routing are formulated and solved as a Multi-path Power Scheduling Optimization (MPSO) problem, which is compared as both linear and nonlinear programming. Performance evaluation of the OMPR approach demonstrates the algorithm's scalability and capability to handle complex scenarios efficiently, including rerouting upon connectivity disruptions. The linear MPSO formulation within the OMPR facilitates real-time implementation compared to nonlinear MPSO by solving an 18-walk P2P exchange in a 100-node community in 0.18 seconds.