TY  - JOUR
AU  - GUO, Ning
AU  - JI, Tuo
AU  - YUAN, Yubo
AU  - ZHOU, Chuang
AU  - XIAO, Xiaolong
AU  - DONG, Shufeng
PY  - 2026
TI  - Three-phase autonomous optimization method for distribution transformer areas based on power distribution and utilization edge agents
JO  - Electric Power Engineering Technology
SN  - 2096-3203
SP  - 46
EP  - 56
VL  - 45
IS  - 8
AB  - 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.
UR  - https://doi.org/10.12158/j.2096-3203.2026.08.005
DO  - 10.12158/j.2096-3203.2026.08.005