WEB可视化技术在电网大数据场景下的应用研究
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摘要
本文针对智能电网大数据场景下传统的可视化方法处理能力和信息表达能力不足的问题展开研究,目的是通过现有先进的可视化手段将电力大数据中蕴藏的关系和规律更直观的呈现出来。本文选取了电力大数据分类监视、输变电设备状态,电网运行、用户用电,气象环境等电力大数据应用场景,寻找用户数据使用痛点并明确分析目标,收集并调研目标的可能影响因素后建立相应的分析模型,为各个场景设计相匹配的可视化技术方案,并着重分析了方案的特色和优势。本文将最新的网络可视化、时空数据可视化、多维数据可视化和Web GIS可视化等Web可视化技术应用到电网大数据展示场景中,为电网大数据应用场景的可视化提供了参考和有益实践,大大提升了电力大数据的利用率和价值。
This paper focuses on the problem of the traditional data visualization methods and the lack of information expression ability in the smart grid big data scenario. The purpose is to present the relationships and rules in the power big data more intuitively through the existing advanced visualization methods. This paper chooses the application scenarios of big data of electric power,such as classified monitoring of big data of electric power,status of transmission and transformation equipment,operation of electric power network,power consumption of users,meteorological environment,etc. It seeks the pain points of user data usage and makes clear the analysis target,collects and investigates the possible influencing factors of the target,establishes the corresponding analysis model,and designs the phases for each scenario. The matching visualization technology scheme is presented,and the characteristics and advantages of the scheme are emphatically analyzed. In this paper,the latest Web visualization technologies,such as network visualization,spatio-temporal data visualization,multi-dimensional data visualization and Web GIS visualization,are applied to the large data display scenario of power grid,which provides a reference and useful practice for the visualization of large data application scenario of power grid,and greatly improves the utilization rate and value of big data of power grid.
This paper focuses on the problem of the traditional data visualization methods and the lack of information expression ability in the smart grid big data scenario. The purpose is to present the relationships and rules in the power big data more intuitively through the existing advanced visualization methods. This paper chooses the application scenarios of big data of electric power,such as classified monitoring of big data of electric power,status of transmission and transformation equipment,operation of electric power network,power consumption of users,meteorological environment,etc. It seeks the pain points of user data usage and makes clear the analysis target,collects and investigates the possible influencing factors of the target,establishes the corresponding analysis model,and designs the phases for each scenario. The matching visualization technology scheme is presented,and the characteristics and advantages of the scheme are emphatically analyzed. In this paper,the latest Web visualization technologies,such as network visualization,spatio-temporal data visualization,multi-dimensional data visualization and Web GIS visualization,are applied to the large data display scenario of power grid,which provides a reference and useful practice for the visualization of large data application scenario of power grid,and greatly improves the utilization rate and value of big data of power grid.
引文
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[18]李刚,刘燕,宋雨,等.基于信息融合的电力大数据可视化预处理方法[J].广东电力,2016,29(12):10-14.LI Gang,LIU Yan,SONG Yu,et al.Visualization pretreatment method for electric power big data based on information fusion[J].Guangdong Electric Power,2016,29(12):10-14.
[19]王金丽,段祥骏,李云江,等.配电网低电压产生原因与综合治理措施[J].供用电,2016,33(07):8-12.WANG Jinli,DUAN Xiangjun,LI Yunjiang,et al.Causes and comprehensive governance measures of low voltage problem in distribution network[J].Distribution&Utilization,2016,33(07):8-12.
[20]侯伟宏,徐丹露,裘愉涛,等.智能变电站SCD文件可视化研究[J].浙江电力,2016,35(01):10-14.HOU Weihong,XU Danlu,QIU Yutao,et al.Research on visualization of substation configuration description file in intelligent substation[J].Zhejiang Electric Power,2016,35(01):10-14.
[2]杨东伟.从电力数据看经济发展趋势[J].华东电力,2013,41(06):1292-1295.YANG Dongwei.Study of economic development trend based on electric power data analysis[J].East China Electric Power,2013,41(06):1292-1295.
[3]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.
[4]中国电机工程学会信息化专委会.中国电力大数据发展白皮书[M].北京:中国电力出版社,2013.
[5]田华.大数据与可视化在电力设备管理中的创新应用[J].电力大数据,2018,21(09):32-35.TIAN Hua.Innovative application of big data and visualization in power equipment management[J].Power Systems and Big Data,2018,21(09):32-35.
[6]孙梦觉,徐敏,牛斌.电力大数据可视化研究设计[J].电力大数据,2017,20(08):61-63+67.SUN Mengjue,XU Min,NIU bin.Research and design of power big data visualization[J].Power Systems and Big Data,2017,20(08):61-63+67.
[7]杜小勇,陈峻,陈跃国.大数据探索式搜索研究[J].通信学报,2015,36(12):77-88.DU Xiaoyong,CHEN Jun,CHEN Yueguo.Exploratory search on big data[J].Journal on Communications,2015,36(12):77-88.
[8]REN L.Research on interaction techniques in information visualization[D].Beijing:The Chinese Academy of Sciences,2009(in Chinese with English abstract).
[9]CARD SK,MACKINLAY JD,SHNEIDERMAN B.Readings in information visualization:using vision to think[M].San Francisco:Morgan-Kaufmann Publishers,1999.1-712.
[10]任磊,杜一,马帅,张小龙,等.大数据可视分析综述[J].软件学报,2014,25(09):1909-1936.REN Lei,DU Yi,MA Shuai,et al.Visual analytics towards big data[J].Journal of Software,2014,25(09):1909-1936
[11]周志光,孙畅,乐丹丹,等.多维时空数据协同可视分析方法[J].计算机辅助设计与图形学学报,2017,29(12):2245-2255.ZHOU Zhiguang,SUN Chang,LE Dandan,et al.Collaborative visual analytics of multi-dimensional and spatio-temporal data[J].Journal of Computer-Aided Design&Computer Graphics,2017,29(12):2245-2255.
[12]温徐敬,王电钢.基于u DC-Builder技术的数据中心可视化技术应用[J].电力大数据2017,20(10):83-87.WEN Xujing,WANG Diangang.Application and innovation on visualization technology of the datacenter based on u DC-Builder technology[J].Power systems and big data,2017,20(10):83-87.
[13]刘华星,杨庚.HTML5---下一代Web开发标准研究[J].计算机技术与发展,2011,21(08):54-58+62LIU Huaxing,YANG Geng.HTML5-next generation web development standard research[J].Computer Technology And Development,2011,21(08):54-58+62.
[14]周航,马曾,贾瑞凤.D3js库在OA管理系统中状态数据可视化的应用[J].计算机与数字工程,2017,45(04):706-711.ZHOU Hang,MA Zeng,JIA Ruifeng.Application of D3js in data visualization method of working status in OA system[J].Computer&Digital Engineering,2017,45(04):706-711.
[15]徐卓揆.基于HTML5、Ajax和Web Service的WebGIS研究[J].测绘科学,2012,37(01):145-147.XU Zhuokui.Research on Web GIS based on HTML5,Ajax and Web Service[J].Science of Surveying and Mapping,2012,37(01):145-147.
[16]王栋.大数据可视化技术在电网企业的应用[J].江苏电机工程,2014,33(06):82-84.WANG Dong.Application of big date visualization technique in power grid enterprise[J].Jiangsu Electrical Engineering,2014,33(06):82-84.
[17]王晓辉,吴克河,肖湘宁,王延平.电力Web GIS平台研究[J].电网技术,2012,36(04):174-178.WANG Xiaohui,WU Kehe,XIAO Xiangning,et al.A study on power Web GIS platform[J].Power System Technology,2012,36(04):174-178.
[18]李刚,刘燕,宋雨,等.基于信息融合的电力大数据可视化预处理方法[J].广东电力,2016,29(12):10-14.LI Gang,LIU Yan,SONG Yu,et al.Visualization pretreatment method for electric power big data based on information fusion[J].Guangdong Electric Power,2016,29(12):10-14.
[19]王金丽,段祥骏,李云江,等.配电网低电压产生原因与综合治理措施[J].供用电,2016,33(07):8-12.WANG Jinli,DUAN Xiangjun,LI Yunjiang,et al.Causes and comprehensive governance measures of low voltage problem in distribution network[J].Distribution&Utilization,2016,33(07):8-12.
[20]侯伟宏,徐丹露,裘愉涛,等.智能变电站SCD文件可视化研究[J].浙江电力,2016,35(01):10-14.HOU Weihong,XU Danlu,QIU Yutao,et al.Research on visualization of substation configuration description file in intelligent substation[J].Zhejiang Electric Power,2016,35(01):10-14.