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基于无线高速数据传输的智能燃料管理应用方案研究

李维聪, 刘霞

李维聪,刘霞.基于无线高速数据传输的智能燃料管理应用方案研究[J].南方能源建设,2021,08(02):56-62.. DOI: 10.16516/j.gedi.issn2095-8676.2021.02.009
引用本文: 李维聪,刘霞.基于无线高速数据传输的智能燃料管理应用方案研究[J].南方能源建设,2021,08(02):56-62.. DOI: 10.16516/j.gedi.issn2095-8676.2021.02.009
LI Weicong,LIU Xia.Research on Application of Wireless High-speed Data Transmission in Intelligent Fuel Management[J].Southern Energy Construction,2021,08(02):56-62.. DOI: 10.16516/j.gedi.issn2095-8676.2021.02.009
Citation: LI Weicong,LIU Xia.Research on Application of Wireless High-speed Data Transmission in Intelligent Fuel Management[J].Southern Energy Construction,2021,08(02):56-62.. DOI: 10.16516/j.gedi.issn2095-8676.2021.02.009
李维聪,刘霞.基于无线高速数据传输的智能燃料管理应用方案研究[J].南方能源建设,2021,08(02):56-62.. CSTR: 32391.14.j.gedi.issn2095-8676.2021.02.009
引用本文: 李维聪,刘霞.基于无线高速数据传输的智能燃料管理应用方案研究[J].南方能源建设,2021,08(02):56-62.. CSTR: 32391.14.j.gedi.issn2095-8676.2021.02.009
LI Weicong,LIU Xia.Research on Application of Wireless High-speed Data Transmission in Intelligent Fuel Management[J].Southern Energy Construction,2021,08(02):56-62.. CSTR: 32391.14.j.gedi.issn2095-8676.2021.02.009
Citation: LI Weicong,LIU Xia.Research on Application of Wireless High-speed Data Transmission in Intelligent Fuel Management[J].Southern Energy Construction,2021,08(02):56-62.. CSTR: 32391.14.j.gedi.issn2095-8676.2021.02.009

基于无线高速数据传输的智能燃料管理应用方案研究

基金项目: 

中国能源建设集团规划设计有限公司科技项目“物联网在智慧电厂的应用研究”资助 中能设科技〔2019〕354号

详细信息
    作者简介:

    李维聪(通信作者)1988-,男,广东五华人,工程师,控制工程硕士,主要从事电力行业热工仪控设计研究的工作(e-mail)liweicong@gedi.com.cn

    刘霞1993-,女,湖北荆州人,设计员,初级工程师,控制科学与工程硕士,主要从事电力行业热工仪控设计研究的工作(e-mail)liuxia@gedi.com.cn

  • 中图分类号: TM611

Research on Application of Wireless High-speed Data Transmission in Intelligent Fuel ManagementEn

  • 摘要:
      目的  目前国内火电行业的智能燃料管理系统中还是使用较为传统的线路传输技术,无论是对于数据的整合处理还是与智能一体化管控云平台互联均欠缺灵活性、可靠性、移动性。数据通讯是电厂管理智能化的重要发展趋势,而更高速的传输速率更是未来智能电厂大数据云计算平台所需建设的目标。为研究更高速的无线数据传输在电力行业应用,将目前最新的无线传输技术在电厂数据传输网络搭建应用并与智能电厂大数据平台融合提供方案参考。
      方法  先介绍目前电厂燃料管理平台的现状及组成,同时介绍目前新一代的5G和WiFi6无线高速传输技术,将其融入现有的电厂管理平台网络架构,并实现高效应用及优化的研究。
      结果  通过分析目前大部分已投运的电厂燃料管理平台存在的问题,研究其高速传输的网络架构有效提高了电厂运行的安全稳定、同时可带来更大的经济收益。
      结论  建设一套无线高速完整的数据传输系统,更有利于智能燃料管理平台的有效安全搭建,并应在项目前期进行设计规划,应用于火力发电行业。
    Abstract:
      Introduction  In domestic thermal power plants, traditional line transmission technology is still used in the fuel management system, which lacks flexibility, reliability and mobility in terms of data integration processing or interconnection with the cloud platform. Data communication is an important development trend of intelligent power plant management, and the higher transmission rate is the goal of building a big data cloud computing platform for smart power plants in the future. This paper provides a reference for studying the application of higher-speed wireless data transmission in power industry, building and applying the latest wireless transmission technology in power plant data transmission network and integrating it with smart power plant big data platform.
      Method  Firstly, this paper introduced the current status and composition of fuel management platform in power plant, and described the 5G and WiFi6 technology, which was integrated into the existing network architecture of power plant management platform, so as to realize efficient application and optimization research.
      Result  By analyzing the problems existing in most of the fuel management platforms in power plants, the high-speed network can effectively improve the operation safety and stability of power plants and bring greater economic benefits.
      Conclusion  The construction of a wireless high-speed and complete data transmission system is more conducive to the effective and safe construction of intelligent fuel management platform, which should be designed and planned in the early stage of the project and applied to thermal power generation industries.
  • 图  1   智能燃料管理系统结构图

    Figure  1.   Structure diagram of intelligent fuel management system

    图  2   高速传输的智能燃料管理系统网络架构图

    Figure  2.   Network diagram of Intelligent fuel management system for high-speed transmission

    图  3   智慧电厂与智能燃料管理系统融合网络架构图

    Figure  3.   Network diagram of smart power plant and intelligent fuel management system integration

    表  1   5G通讯技术参数对比

    Table  1   5G communication technology parameters comparation

    技术参数4G5G
    传输速率/Gbps0.010.1~1.0
    移动性/(km·h-1350500
    时延/ms20~30低至1
    单位带宽传输速率1倍3倍
    下载: 导出CSV

    表  2   WiFi6通讯技术对比

    Table  2   WiFi6 communication technology comparation

    技术参数WiFi5WiFi6
    通信协议802.11ac802.11ax
    工作频段52.45
    最大频宽/MHz80/160160
    带宽/Mbps433/8671 200
    多用户技术下行上行/下行
    下载: 导出CSV
  • [1] 王会祥,王秋明. 发电企业的经营模拟分析与市场交易策略 [J]. 华电技术,2018,40(7):64-67+80.

    WANGH X, WANGQ M. Business strategy simulation and trading strategy of power generation enterprises [J]. Huadian Technology, 2018, 40 (7): 64-67+80.

    [2] 何亮. 火电厂燃料智能化系统项目质量和评价研究 [D]. 北京:华北电力大学(北京),2016.

    HEL. Research on the quality and evaluation for fuel intelligent system project of thermal power plant [D]. Beijing: North China Electric Power University, 2016.

    [3] 韩月丽. 绥中发电公司燃料库存项目管理研究 [D]. 保定:华北电力大学,2014.

    HANY L. Research on Shenhua Guohua Suizhong Power Genreration Co., Ltd. fuel inventory project management [D]. Baoding: North China Electric Power University, 2014.

    [4] 凌海,罗颖坚. 智能电厂规划建设内容探讨 [J]. 南方能源建设,2017,4(增刊1):9-12.

    LINGH, LUOY J. Discussion on the content of planning and construction of intelligent power plant [J]. Southern Energy Construction, 2017, 4 (Supp.1): 9-12.

    [5] 孙继平, 陈晖升. 智慧矿山与5G和WiFi6 [J]. 工矿自动化,2019,45(10):1-4.

    SUNJ P, CHENH S. Smart mine with 5G and WiFi6 [J]. Industry and Mine Automation, 2019, 45 (10): 1-4.

    [6] 孙继平. 煤矿智能化与矿用5G [J]. 工矿自动化,2020,46(8):1-7.

    SUNJ P. Coal mine intelligence and mine-used 5G [J]. Industry and Mine Automation, 2020, 46 (8): 1-7.

    [7] 赵俊杰,冯树臣,刘志宏,等. 5G电力网络切片技术在燃煤智慧电厂生产管控应用分析 [J]. 能源科技,2020,18(2):5-10.

    ZHAOJ J, FENGS C, LIUZ H, et al. Application analysis of production management and control of coal-fired intelligent power plant based on 5G power network slicing technology [J]. Energy Science and Technology, 2020, 18 (2): 5-10.

    [8] 张雪亚,张建伟. 数字无线局域网的标准介绍和构网关键技术研究 [J]. 微型电脑应用,2018,34(8):10-13.

    ZHANGX Y, ZHANGJ W. Research on the construction of digital wireless lan [J]. Microcomputer Applications, 2018, 34 (8): 10-13.

    [9] 江波. 5G技术和WiFi6技术在高校智慧校园建设中的应用探讨 [J].数字技术与应用,2020,38(4):28-30.

    JIANGB. Discussion on the application of 5G technology and wifi6 technology in the construction of smart campus in colleges and universities [J]. Digital Technology & Application, 2020, 38 (4): 28-30.

    [10] 孔卉茹. 低热值煤燃料的配煤优化控制系统开发 [D]. 太原:山西大学,2017.

    KONGH R. Development of optimized coal blending control system for calorific value coal [D]. Taiyuan: Shanxi University, 2017.

    [11] 王小虎. 数字化燃料管理系统技术研究 [J]. 南方能源建设,2017,4(1):53-56.

    WANGX H. Research on digital fuel management system [J]. Southern Energy Construction, 2017, 4 (1): 53-56.

    [12] 郝敬亚. 群体智能算法在电厂燃料管理系统中的应用研究 [D]. 保定:华北电力大学,2012.

    HAOJ Y. The application and research of swam intelligence algorithms in the power plant coal management [D]. Baoding: North China Electric Power University, 2011.

    [13] 张广宏. 数字燃煤环境下发电企业燃煤库存管理优化研究 [D]. 北京:华北电力大学(北京),2016.

    ZHANGG H. Research on optimization of coal inventory management of power plants under digital coal [D]. Beijing: North China Electric Power University, 2016.

    [14] 夏金凤. 基于元胞遗传算法的无线电能传输网链路优化技术 [D].重庆:重庆大学,2017.

    XIAJ F. Path optimization technology of wireless power transfer networks based on cellular genetic algorithm [D]. Chongqing: Chongqing University, 2017.

    [15] 王晓雄,王景超,裴顺. 浅谈智能电厂规划建设 [J]. 南方能源建设,2017,4(3):30-34.

    WANGX X, WANGJ C, PEIS. Preliminary analysis of smart power plant planning and construction [J]. Southern Energy Construction, 2017, 4 (3): 30-34.

    [16] 张国平. 火力发电厂劣质煤掺烧技术探讨及应用 [J]. 陕西电力,2013,41(3):83-85.

    ZHANGG P. Discussion and appllication of inferior coal blending technology in thermal power plant [J]. Shaanxi Electric Power, 2013, 41 (3): 83-85.

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出版历程
  • 收稿日期:  2020-11-09
  • 修回日期:  2021-01-06
  • 刊出日期:  2021-06-24

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