A scalable energy internet approach for hop regulated peer-to-peer power trading with connectivity and preference constraints

Incentives to maximize Peer-to-Peer (P2P) power trading and the establishment of consumer-friendly distributed power markets are essential contributions to the decarbonization of the power sector. This paper presents a Connectivity and Preference Constrained Hop-Regulated Approach for Peer-to-Peer Trading (CPHPT) in sparsely connected communities with reduced infrastructure requirements. The CPHPT approach leverages graph theory to optimize P2P subscriber matching by regulating the maximum hops between the nodes in each routed path of P2P exchange. Simulations using real-world datasets in a 10-home community demonstrate that the CPHPT increases community participation by 29.49%, with P2P power exchanges comparable to full connectivity at reduced infrastructure requirements. When scaled to a 100-home community, the CPHPT approach achieves a marginal performance difference of 2.71% compared to full connectivity while lowering the connectivity infrastructure by 93.4%. The CPHPT approach has a mean runtime of 8.9 s for a 3-h window with 30-min intervals in a 100-home community, indicating its scalability and feasibility for real-time implementation.