引用本文:钟加勇,王雪文,刘丁豪,等.面向配电网计算推演的智能终端部署优化方法[J].电力系统保护与控制,2026,54(03):177-187.
ZHONG Jiayong,WANG Xuewen,LIU Dinghao,et al.An optimization method for smart terminal deployment oriented to computational simulation of distribution networks[J].Power System Protection and Control,2026,54(03):177-187
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面向配电网计算推演的智能终端部署优化方法
钟加勇,王雪文,刘丁豪,等
1.国网重庆市电力公司电力科学研究院,重庆 401123;2.重庆大学,重庆 400044
摘要:
当前配电网智能终端部署存在感知终端配置覆盖水平不足与重复部署共存的问题,且“一台区一终端”尚未实现,缺乏智能配电终端配置标准,导致运维工作量增加。对此,提出了面向智能配电网计算推演的终端部署优化方法。首先,提出“最小化精准采集 + 数字系统计算推演”的智能终端部署优化方法,通过优化终端部署、强化专业协同、深化数据应用的“三措并举”策略,制定面向智能配电终端部署的差异化配置策略。然后,基于上述部署优化方法提出了面向智能配电网的计算推演方法,通过建立基于智能终端的配电网计算推演流程,提升配电网智能化水平,支持分布式能源、储能和电动汽车的发展。最后,通过仿真实验证明了所提方法的有效性。
关键词:  计算推演  智能配电终端  精准数据采集  智能配电网
DOI:10.19783/j.cnki.pspc.250228
分类号:
基金项目:重庆市重点研发项目资助“基于电网数字空间的电网生产业务流程优化方法研究”(cstc2024ycjh-bgzxm0191);国网重庆市电力公司科技项目资助“面向电网数字化转型的数字空间构建方法与应用研究”(2024渝电科技15#)
An optimization method for smart terminal deployment oriented to computational simulation of distribution networks
ZHONG Jiayong1, WANG Xuewen1, LIU Dinghao1, CUI Qiushi2, RAN Maoju1
1. State Grid Chongqing Electric Power Research Institute, Chongqing 401123, China; 2. Chongqing University, Chongqing 400044, China
Abstract:
At present, the deployment of smart distribution network terminals suffers from the coexistence of insufficient coverage of sensing terminals and redundant installations. Moreover, the concept of “one terminal per distribution area” has not yet been achieved and standardized configurations guidelines for smart terminals are lacking, resulting in increased operational and maintenance workloads. To address these issues, an optimization method for terminal deployment oriented to computational simulation of smart distribution networks is proposed. First, a smart terminal deployment optimization method based on the concept of “minimal precise data acquisition combined with digital system-based computational simulation” is presented. By adopting a three-pronged strategy that includes optimizing terminal deployment, strengthening interdisciplinary coordination, and deepening data utilization, a differentiated configuration strategy for the deployment of smart distribution terminals is formulated. Then, based on the proposed deployment optimization method, a computational simulation approach for smart distribution networks is established. By constructing a distribution network computational simulation framework supported by smart terminals, the intelligence level of distribution networks is enhanced, thereby facilitating the integration and development of distributed energy resources, energy storage systems, and electric vehicles. Finally, the effectiveness of the proposed method is demonstrated through simulations.
Key words:  computational extrapolation  smart distribution terminals  accurate data acquisition  smart distribution networks
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