马群, 于佳. 面向新型电力系统的感知层网络技术研究[J]. 山东电力技术, 2023, 50(6): 13-19. DOI: 10.20097/j.cnki.issn1007-9904.2023.06.003
引用本文: 马群, 于佳. 面向新型电力系统的感知层网络技术研究[J]. 山东电力技术, 2023, 50(6): 13-19. DOI: 10.20097/j.cnki.issn1007-9904.2023.06.003
MA Qun, YU Jia. Research on Sensing Layer Network Technology for New Power System[J]. Shandong Electric Power, 2023, 50(6): 13-19. DOI: 10.20097/j.cnki.issn1007-9904.2023.06.003
Citation: MA Qun, YU Jia. Research on Sensing Layer Network Technology for New Power System[J]. Shandong Electric Power, 2023, 50(6): 13-19. DOI: 10.20097/j.cnki.issn1007-9904.2023.06.003

面向新型电力系统的感知层网络技术研究

Research on Sensing Layer Network Technology for New Power System

  • 摘要: 随着新型电力系统的发展,配电网低压侧测控、分布式新能源快速功率群控等新业务不断涌现。传统以采集为主的感知层通信网需要承载控制业务,对感知层通信的带宽、实时性、可靠性和安全性等方面提出更高要求。针对这种情况,分析新型电力系统下的感知层网络技术方案和安全方案,在变电站、配电房等电力业务集中的站点,统筹建设感知层网络,实现本地宽窄带有线和无线信号覆盖、统一管理、安全接入,避免无线资源抢占和有线网络重复建设。依托物联网总体架构从覆盖、性能、安全三个方面增强本地网络承载新型电力系统分布式新能源的控制能力,提升感知层网络深度与广度,降低电网感知成本。

     

    Abstract: With the development of new power systems,new businesses such as low-voltage side measurement and control of the distribution network and distributed new energy rapid power group control are constantly emerging.The traditional acquisition sensing layer communication network needs to carry control services,which puts forward higher requirements for the bandwidth,real-time,reliability and security of the sensing layer communication.The sensing layer network technology and security schemes for the new power system were analyzed.In substations,distribution rooms,and other sites where power services are concentrated,a sensing layer network should be built as a whole to achieve local broadband wired and wireless signal coverage,unified management,and secure access,avoiding wireless resource preemption and redundant construction of wired networks.Relying on the overall architecture of the Internet of Things,it has enhanced the control ability of local networks to carry distributed new energy from new power systems in terms of coverage,performance,and security,improved the depth and breadth of the sensing layer network,and reduced the cost of grid sensing.

     

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