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基于源-网-荷互动环境的智能变电站优化组网通信网络的构建。

Construction of Intelligent Substation-Optimized Networking Communication Network Based on Source-Network-Load Interaction Environment.

机构信息

Department of Evaluation Center, Economic and Technological Research Institute of State Grid Fujian Electric Power Co. Ltd, Fuzhou 350000, Fujian, China.

出版信息

J Environ Public Health. 2022 Sep 28;2022:4730233. doi: 10.1155/2022/4730233. eCollection 2022.

Abstract

Smart grids, which possess flexibility, cleanliness, safety, economy, and friendliness, have drawn a lot of attention from all over the world in an era of rapid social and economic development, power technology change, and energy and environmental constraints. However, there are still issues with the design, installation, and operation of smart substations, such as insufficient LAN integration, difficulty quantifying network performance, and inability to keep track of communication. The basic meaning and key technologies of substation communication standards are used as the research object in this paper, and the basic attributes of substation data flow, such as source, type, and function, are qualitatively analyzed. The mathematical model that is most closely fitted is 2.8% more effective. The research object is the topology of the process bus. Through the comparison of various solutions, including star topology, ring topology, bus topology, and mesh topology, the advantages and disadvantages of each topology networking scheme are revealed along with the particular functional requirements of the substation process layer. Further discussion is given to the crucial topology-related technologies of network congestion and flow control.

摘要

智能电网在社会经济快速发展、电力技术变革以及能源环境约束的时代背景下,以其灵活性、清洁性、安全性、经济性和友好性备受关注。然而,智能变电站在设计、安装和运行方面仍存在一些问题,例如局域网集成不足、难以量化网络性能以及无法跟踪通信等。本文以变电站通信标准的基本含义和关键技术为研究对象,定性分析了变电站数据流的基本属性,如来源、类型和功能。所建数学模型的拟合效果提高了 2.8%。研究对象是过程总线的拓扑结构。通过比较星型拓扑、环形拓扑、总线拓扑和网状拓扑等各种解决方案,揭示了每种拓扑网络方案的优缺点,以及变电站过程层的特殊功能要求。进一步讨论了与网络拥塞和流量控制相关的关键拓扑技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9141/9534685/13a0553322fa/JEPH2022-4730233.001.jpg

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