Three-phase autonomous optimization method for distribution transformer areas based on power distribution and utilization edge agents

The introduction of edge intelligence technology to offload partial power services to the distribution station side serves as an effective technical pathway for distributed smart grid construction at the medium- and low-voltage distribution network level. This paper proposes a power service-oriented distribution and consumption edge intelligence agent, along with a three-phase autonomous optimization method for photovoltaic-storage integrated distribution transformer areas. Firstly, the definition of the distribution and consumption edge intelligence agent is established, with its architecture designed through domain-driven business modeling and event-driven state service mechanisms. Secondly, to address prominent three-phase asymmetry in distribution transformer areas, an improved three-phase distribution network branch power flow model is derived via convex relaxation. Finally, a three-phase coordinated multi-objective optimization model for photovoltaic-storage distribution transformer areas is developed based on the improved power flow model, integrated with the edge agent's state service mechanism for dynamic service processing. This achieves autonomous edge-side management encompassing localized state perception, event identification, optimized control, and closed-loop feedback. Case studies on a 21-node distribution transformer area and engineering validations demonstrate that the proposed edge intelligence agent effectively handles service requirements, while the proposed model and optimization strategy exhibit engineering-applicable accuracy and control effectiveness.