基于配用电边缘智能体的台区三相自治优化方法OA
Three-phase autonomous optimization method for distribution transformer areas based on power distribution and utilization edge agents
引入边缘智能技术,将部分电力业务下沉至台区侧,是分布式智能电网建设中低压配电网层面的有效技术路径.文中提出一种面向电力业务的配用电边缘智能体,并基于此提出一种光储台区三相自治优化方法.首先,给出配用电边缘智能体定义并设计其体系架构,采用领域驱动方法构建业务模型,设计事件驱动式状态服务机制;其次,针对台区突出的三相不对称性,利用凸松弛推导改进的三相配电网支路潮流模型;最后,基于改进潮流模型建立台区三相光储协同多目标优化模型,并结合边缘智能体状态服务机制进行业务动态处理,从而实现边缘侧本地化状态感知、事件识别、优化调控与反馈闭环的自治管理.基于 21节点台区算例与工程实践进行分析,结果表明,所设计的边缘智能体能有效处理业务需求,所提模型及优化策略具备工程应用的精确性与控制有效性.
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.
郭宁;嵇托;袁宇波;周创;肖小龙;董树锋
国网江苏省电力有限公司电力科学研究院,江苏 南京 211103国网江苏省电力有限公司,江苏 南京 210024国网江苏省电力有限公司电力科学研究院,江苏 南京 211103浙江大学电气工程学院,浙江 杭州 310027国网江苏省电力有限公司电力科学研究院,江苏 南京 211103浙江大学电气工程学院,浙江 杭州 310027
信息技术与安全科学
边缘智能智能体三相配电网台区自治事件驱动凸松弛
edge intelligenceagentthree-phase distribution networkdistribution transformer area autonomyevent-drivenconvex relaxation
《电力工程技术》 2026 (8)
46-56,11
本文得到国网江苏省电力有限公司科技项目(J2023114)资助
评论