ElectricVIS: visual analysis system for power supply data of smart city

  • Qiang LuEmail author
  • Wenqiang Xu
  • Haibo Zhang
  • Qingpeng Tang
  • Jie Li
  • Rui Fang


Smart grids provide a key driver for smart city development. The smart city power supply data visualization can realize the power characteristic information of various attributes and operating states in the online monitoring data of massive power equipments in a graphical and visual presentation, which provides a powerful guarantee for timely and effective monitoring and analysis of equipment operating status. However, with the rapid development of smart cities, the complexity of urban power data and the ever-increasing amount of data hinder the power managers’ understanding and analysis of the power supply situation. Based on the smart city power supply data, a novel visual analysis system ElectricVis for urban power supply situation is proposed, which can interactively analyze large-scale urban power supply data. ElectricVis reduces the difficulty of understanding urban power supply situations by adopting novel visual graphic designs and time patterns that display power data in multiple scales. ElectricVis also provides different visual views and interaction methods for interrelated hierarchical data in urban power data, which is critical for detecting the cause of anomalous data. Finally, we evaluated our system through case studies and analysis by power experts.


Smart city Visual analysis Urban power supply Graphic design 



This work was supported in part by the Natural Science Foundation of Anhui Province of China under Grant 1708085MF158, in part by the National Natural Science Foundation of China under Grants 61472115, 61672201, in part by the Visiting Scholar Researcher Program at North Texas University through the State Scholarship Fund of the China Scholarship Council under Grant 201706695044, and in part by the Key Project of Transformation and Industrialization of Scientific and Technological Achievements of Intelligent Manufacturing Technology Research Institute of Hefei University of Technology under Grant IMICZ2017010.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Computer and InformationHefei University of TechnologyHefeiChina
  2. 2.Anhui Province Key Laboratory of Industry Safety and Emergency TechnologyHefei University of TechnologyHefeiChina
  3. 3.Hefei Engineering Research Center of Electric Power Data ApplicationHefeiChina
  4. 4.State Grid Hefei Power Supply CompanyHefeiChina
  5. 5.University of Shanghai for Science and TechnologyShanghaiChina

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