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一种基于电力线路布局优化的城市供电数据可视分析方法

A Method for Visual Analysis of Urban Power Supply Data Based on Power Line Layout Optimization

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【作者】 路强张海波YUAN Xiao-hui陈晨

【Author】 LU Qiang;ZHANG Hai-bo;YUAN Xiao-hui;CHEN Chen;VCC Division, School of Computer and Information, Hefei University of Technology;Hefei Engineering Research Center of Electric Power Data Application;Department of Computer Science and Engineering, University of North Texas;State Grid Hefei Electric Power Supply Company;

【机构】 合肥工业大学计算机与信息学院VCC研究室合肥市电力大数据应用工程技术研究中心北得克萨斯大学计算机科学与工程学院国网安徽省电力公司合肥供电公司

【摘要】 电力数据可视化可以实现海量电力设备在线监测数据中各种属性、运行状态等电力特征信息以图形、图像化直观呈现,为设备运行状态的及时、有效监控分析提供有力保障。基于城市供电数据,提出一种城市供电态势的可视分析方法。首先根据供电系统中的变电站数据对总体供电态势进行可视化,然后根据供电线路数据对线路进行基于多标准约束的布局优化并对其进行可视化编码,最后根据线路的附属关系对线路下挂载的用户进行可视化编码。设计了一套可视分析系统,旨在方便用户探索分析某一区域的供电态势。基于上海市城市供电数据的案例分析表明,该方法可以有效地反映某一区域内的总体供电态势和具体供电细节。

【Abstract】 The visualization of power data can realize the online monitoring of different power features including various attributes and operating status, etc., which can be graphically and visually presented to provide a powerful guarantee for the timely and effective monitoring and analysis of equipment operation status. Based on the urban power supply data, a method for the visual analysis of power supply situation in the city is proposed. Firstly, the overall power supply situation is visualized based on the substation data in the power supply system. Then, the layout is optimized based on multi-criteria constraints and visually coded according to the power supply line data. Finally,according to the relation of lines, the visualized coding is conducted on the users of different lines. A visual analysis system has also been designed to facilitate the user’s exploration and analysis of the power supply situation in a certain area. Case studies based on Shanghai City Power Supply data show that the method can effectively reflect the overall power supply situation and specific power supply details in a certain area.

【基金】 安徽省自然科学基金项目(1708085MF158);国家自然科学基金项目(61602146);国家留学基金项目(201706695044);合肥工业大学智能制造技术研究院科技成果转化及产业化重点项目(IMICZ2017010)
  • 【文献出处】 图学学报 ,Journal of Graphics , 编辑部邮箱 ,2019年01期
  • 【分类号】TM76
  • 【被引频次】7
  • 【下载频次】101
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