一种基于图的电力数据可视分析方法
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摘要
将可视化分析技术应用于电力系统可以有效地解决由电力系统发展带来的海量电力数据分析及显示等问题,从而辅助电力部门进行决策。针对城市电力数据,提出了一种基于图的电力数据可视分析方法。首先对城市供电数据进行预处理;然后对城市供电网络进行建模;最后根据可视化原则针对城市供电网络中的多种电力数据设计不同的可视化方法进行可视化与分析。根据合肥市某区域的电力数据的案例分析,表明该方法可以有效地反映某一区域的电力系统运行状态和电力客户分布情况。
Applying visual analysis technology to the power system can effectively solve the massive power data analysis and display problems caused by the development of the power system, thereby assisting the power sector in making decisions. Based on the city power data, a graph-based power data visual analysis method is proposed. Firstly, the urban power supply data is preprocessed, then the urban power supply network is modeled. Finally, according to the visualization principle, different visualization methods are designed for the visualization and analysis of multiple power data in the urban power supply network. Based on the case study of power data in a certain area of Hefei City, it is shown that this method can effectively reflect the operating status of power systems and the distribution of power customers in a certain area.
Applying visual analysis technology to the power system can effectively solve the massive power data analysis and display problems caused by the development of the power system, thereby assisting the power sector in making decisions. Based on the city power data, a graph-based power data visual analysis method is proposed. Firstly, the urban power supply data is preprocessed, then the urban power supply network is modeled. Finally, according to the visualization principle, different visualization methods are designed for the visualization and analysis of multiple power data in the urban power supply network. Based on the case study of power data in a certain area of Hefei City, it is shown that this method can effectively reflect the operating status of power systems and the distribution of power customers in a certain area.
引文
[1]DRAPER G M,LIVNAT Y,RIESENFELD R F.Asurvey of radial methods for information visualization[J].IEEE Transactions on Visualization and Computer Graphics,2009,15(5):759-776.
[2]DU Y,MA C,WU C,et al.A visual analytics approach for station-based air quality data[J].Sensors,2017,17(1):30.
[3]CHO M,KIM B,BAE H J,et al.Stroscope:Multi-scale visualization of irregularly measured time-series data[J].IEEE Transactions on Visualization and Computer Graphics,2014,20(5):808-21.
[4]SANFTMANN H,WEISKOPF D.3D scatterplot navigation[J].IEEE Transactions on Visualization and Computer Graphics,2012,18(11):1969-1978.
[5]戚陆越,吴升.时间序列数据可视化研究综述[J].微型机与应用,2015,34(12):7-10.
[6]GEGNER K M,OVERBYE T J,SHETYE K S,et al.Visualization of power system wide-area,time varying information[C]//Power and Energy Conference at Illinois(PECI).New York:IEEE Press,2016:1-4.
[7]DUTTA S,OVERBYE T J.Information processing and visualization of power system wide area time varying data[C]//Computational Intelligence Applications In Smart Grid(CIASG).New York:IEEE Press,2013:6-12.
[8]LI B,LIU W Y,XING J,et al.The opengl-based visualization of power system flow and alarm[C]//Power and Energy Engineering Conference(APPEEC).New York:IEEE Press,2012:1-4.
[9]ANDRIENKO G L,ANDRIENKO N V,DYKES J,et al.Geovisualization of dynamics,movement and change:Key issues and developing approaches in visualization research[J].Information Visualization,2008,7(3):173-180.
[10]NUSRAT S,KOBOUROV S.The state of the art in cartograms[J].Computer Graphics Forum,2016,35(3):619-642.
[11]MA Y,LIN T,CAO Z,et al.Mobility viewer:An eulerian approach for studying urban crowd flow[J].IEEE Transactions on Intelligent Transportation Systems,2016,17(9):2627-2636.
[12]WANG Z,YE T,LU M,et al.Visual exploration of sparse traffic trajectory data[J].IEEE Transactions on Visualization and Computer Graphics,2014,20(12):1813-1822.
[13]SUN G,LIANG R,QU H,et al.Embedding spatio-temporal information into maps by route-zooming[J].IEEE Transactions on Visualization and Computer Graphics,2017,23(5):1506-1519.
[2]DU Y,MA C,WU C,et al.A visual analytics approach for station-based air quality data[J].Sensors,2017,17(1):30.
[3]CHO M,KIM B,BAE H J,et al.Stroscope:Multi-scale visualization of irregularly measured time-series data[J].IEEE Transactions on Visualization and Computer Graphics,2014,20(5):808-21.
[4]SANFTMANN H,WEISKOPF D.3D scatterplot navigation[J].IEEE Transactions on Visualization and Computer Graphics,2012,18(11):1969-1978.
[5]戚陆越,吴升.时间序列数据可视化研究综述[J].微型机与应用,2015,34(12):7-10.
[6]GEGNER K M,OVERBYE T J,SHETYE K S,et al.Visualization of power system wide-area,time varying information[C]//Power and Energy Conference at Illinois(PECI).New York:IEEE Press,2016:1-4.
[7]DUTTA S,OVERBYE T J.Information processing and visualization of power system wide area time varying data[C]//Computational Intelligence Applications In Smart Grid(CIASG).New York:IEEE Press,2013:6-12.
[8]LI B,LIU W Y,XING J,et al.The opengl-based visualization of power system flow and alarm[C]//Power and Energy Engineering Conference(APPEEC).New York:IEEE Press,2012:1-4.
[9]ANDRIENKO G L,ANDRIENKO N V,DYKES J,et al.Geovisualization of dynamics,movement and change:Key issues and developing approaches in visualization research[J].Information Visualization,2008,7(3):173-180.
[10]NUSRAT S,KOBOUROV S.The state of the art in cartograms[J].Computer Graphics Forum,2016,35(3):619-642.
[11]MA Y,LIN T,CAO Z,et al.Mobility viewer:An eulerian approach for studying urban crowd flow[J].IEEE Transactions on Intelligent Transportation Systems,2016,17(9):2627-2636.
[12]WANG Z,YE T,LU M,et al.Visual exploration of sparse traffic trajectory data[J].IEEE Transactions on Visualization and Computer Graphics,2014,20(12):1813-1822.
[13]SUN G,LIANG R,QU H,et al.Embedding spatio-temporal information into maps by route-zooming[J].IEEE Transactions on Visualization and Computer Graphics,2017,23(5):1506-1519.