核电企业面向开放架构的大数据平台的研究与应用
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摘要
本文对核电企业建设大数据平台的背景、建设目标以及预期收益进行分析,阐述了大数据平台架构设计需要遵循的前瞻性、可扩展、开放性、高性能、稳定性、安全性、易维护、实用性、高可用、统一管理等原则。以面向开放为架构设计准则,采用分层架构,详细分析了数据产生层、数据交换层、数据计算层、数据存储层、数据服务层、数据应用层等各个层次所起到的作用以及各个层次所使用到的具体技术方案。文章以基于大数据与机器学习的信函智能分发功能以及基于实时计算的阀门缺陷分类统计这两个案例为例,阐述了大数据技术平台在核电企业实际业务中的应用场景,介绍了各自的详细技术架构和应用效果,说明了大数据技术平台的应用对核电企业所带来的变化与业务收益。
This paper analyzes the background,construction goals,and expected benefits of big data platform of the nuclear power enterprise's construction,and expounds the forward-looking,scalable,open,high performance,stability,security,and easy maintenance,practicality,high availability,unified management and other principles that architecture design must follow. With the open-architectureoriented design guidelines and the layered architecture,which provide detailed analysis of the roles and levels of the data generation layer,data exchange layer,data computing layer,data storage layer,data service layer,and data application layer. The specific technical solution used. The article uses the intelligent distribution function of letters based on big data and machine learning,and the classification and statistics of valve defects based on real-time calculation. These two cases are examples,illustrating the application scenarios of big data technology platform in the actual business of nuclear power enterprises. The detailed technical framework and application effects are introduced,and the changes and business benefits brought by the application of big data technology platform to nuclear power enterprises are explained.
This paper analyzes the background,construction goals,and expected benefits of big data platform of the nuclear power enterprise's construction,and expounds the forward-looking,scalable,open,high performance,stability,security,and easy maintenance,practicality,high availability,unified management and other principles that architecture design must follow. With the open-architectureoriented design guidelines and the layered architecture,which provide detailed analysis of the roles and levels of the data generation layer,data exchange layer,data computing layer,data storage layer,data service layer,and data application layer. The specific technical solution used. The article uses the intelligent distribution function of letters based on big data and machine learning,and the classification and statistics of valve defects based on real-time calculation. These two cases are examples,illustrating the application scenarios of big data technology platform in the actual business of nuclear power enterprises. The detailed technical framework and application effects are introduced,and the changes and business benefits brought by the application of big data technology platform to nuclear power enterprises are explained.
引文
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[17]周升,陶敏,徐朋,等.基于SG-UAP的实时/历史数据平台统一访问方法研究[J].浙江电力,2016,350(04):70-73.ZHOU Sheng,TAO Min,XU Peng,et al.Study on universe access method of real-time/historical data platform based on SG-UAP[J].Zhejiang Electric Power,2016,35(04):70-73.
[2]陈敬德,盛戈皞,吴继健,等.大数据技术在智能电网中的应用现状及展望[J].高压电器,2018,54(01):35-43.CHEN Jingde,SHENG Gehao,WU Jijian,et al.Application status and prospect of big data technology in smart grid[J].High Voltage Apparatus,2018,54(01):35-43.
[3]王玮,刘荫,于展鹏,等.电力大数据环境下大数据中心架构体系设计[J].电力信息与通信技术,2016,14(01):1-6.WANG Wei,LIU Yin,YU Zhanpeng,et al.System design of the big data center architecture in electric power big data environment[J].Electric Power Information and Communication Technology,2016,14(01):1-6.
[4]李占英.智能配电网大数据应用技术与前景分析[J].电力大数据,2017,20(11):18-20.LI Zhanying.Intelligent power distribution network and prospect analysis technology of data application[J].Power Systems and Big Data,2017,20(11):18-20.
[5]彭小圣,邓迪元,程时杰,等.面向智能电网应用的电力大数据关键技术[J].中国电机工程学报,2015,35(03):503-511.PENG Xiaosheng,DENG Diyuan,CHENG Shijie,et al.Key Technologies of electric power big data and its application prospects in smart grid[J].Proceedings of the CSEE,2015,35(03):503-511.
[6]朱朝阳,王继业,邓春宇.电力大数据平台研究与设计[J].电力信息与通信技术,2015,13(06):1-7.ZHU Chaoyang,WANG Jiye,DENG Chunyu.Research and design of electric power big data platform[J].Electric Power Information and Communication Technology,2015,13(06):1-7.
[7]袁捷.贵州电网大数据应用探讨[J].电力大数据,2017,20(12):4-7.YUAN Jie.Discussion on application of big data in Guizhou power grid[J].Power Systems and Big Data,2017,20(12):4-7.
[8]张帆.智慧电厂一体化大数据平台关键技术及应用分析[J].华电技术,2017,39(02):1-3+7+76.ZHANG Fan.Intelligent power plant integrated big data platform key technology and application analysis[J].Huadian Technology,2017,39(02):1-3+7+76.
[9]曲朝阳,张艺竞,王永文,等.基于Spark框架的能源互联网电力能源大数据清洗模型[J].电测与仪表,2018,55(02):39-44.QU Chaoyang,ZHANG Yijing,WANG Yongwen,et al.Big energy data cleaning model for energy internet based on spark framework[J].Electric Measurement&Instrumentation,2018,55(02):39-44.
[10]张冰玉.基于数据挖掘技术的短期电力负荷预测[J].电力大数据,2017,20(10):18-21.ZHANG Bingyu.Prediction of short-term power load based on data mining technology[J].Power Systems and Big Data,2017,20(10):18-21.
[11]曾四鸣.大数据挖掘技术在电力行业中的应用[J].电力大数据,2017,20(09):81-84.ZENG Siming.The application of big data mining(DM)technology in power system[J].Power Systems and Big Data,2017,20(09):81-84.
[12]杨华飞,李栋华,程明.电力大数据关键技术及建设思路的分析和研究[J].电力信息与通信技术,2015,13(01):7-10.YANG Huafei,LI Donghua,CHENG Ming.Analysis and Research of Key Technologies and Construction Ideas of Power Big Data[J].Electric Power Information and Communication Technology,2015,13(01):7-10.
[13]曹皖诚,汤少卿,尤鋆.大数据平台在电力系统中的应用研究[J].江苏科技信息,2016(29):53-56+71.CAO Wancheng,TANG Shaoqing,YOU Jun.Research on the application of big data platform in power system[J].Jiangsu Science and Technology Information,2016(29):53-56+71.
[14]李佳玮,郝悍勇,李宁辉.电网企业大数据技术应用研究[J].电力信息与通信技术,2014,12(12):20-25.LI Jiayu,HAO Hanyong,LI Ninghui.Research on the application of big data in power grid corporation[J].Power Information and Communication Technology,2014,12(12):20-25.
[15]赵云山,刘焕焕.大数据技术在电力行业的应用研究[J].电信科学,2014,30(01):57-62.ZHAO Yunshan,LIU Huanhuan.Research on application of big data technique in electricity power industry[J].Telecommunication Science,2014,30(01):57-62.
[16]王志坚.基于大数据平台的电力营销信息化建设分析[J].内蒙古电力技术,2016,34(04):17-22.WANG Zhijian.Informatization construction of power marketing based on big data platform[J].Inner Mongolia Electric Power,2016,34(04):17-22.
[17]周升,陶敏,徐朋,等.基于SG-UAP的实时/历史数据平台统一访问方法研究[J].浙江电力,2016,350(04):70-73.ZHOU Sheng,TAO Min,XU Peng,et al.Study on universe access method of real-time/historical data platform based on SG-UAP[J].Zhejiang Electric Power,2016,35(04):70-73.