DocumentCode :
1474384
Title :
A Data-Driven Approach to Interactive Visualization of Power Systems
Author :
Zhu, Jun ; Zhuang, Eric ; Ivanov, Chavdar ; Yao, Ziwen
Author_Institution :
Power Inf. LLC, Bothell, WA, USA
Volume :
26
Issue :
4
fYear :
2011
Firstpage :
2539
Lastpage :
2546
Abstract :
Information visualization appears to be a promising technique for improving the business practices in today´s electric power industry. The legacy power system visualization tools, however, restrict the visualization process to follow a limited number of pre-defined patterns created by human designers, thus hindering users´ ability to discover. This paper proposes a data-driven approach to interactive visualization of power systems. The proposed approach relies on developing powerful data manipulation algorithms to create visualizations based on the characteristics of empirically or mathematically derived data. Based on this approach, a data-driven model exploratory tool has been developed to enable users to visualize the power system´s physical/electrical configurations at various levels and from different perspectives. The conducted case studies have demonstrated that the data-driven approach could result in an interactive and user-driven power system visualization tool that fosters scientific understanding and insight, therefore unleashing the power of visualization.
Keywords :
data visualisation; power engineering computing; power system simulation; business practice; common information model; data driven interactive visualization; data driven model; electric power industry; electrical configuration; information visualization; legacy power system visualization tool; physical configuration; power system interactive visualization; powerful data manipulation algorithms; predefined patterns; Data visualization; Pattern matching; Power system dynamics; Smart grids; Visual analytics; Common Information Model (CIM); Smart Grid; data-driven; interactive visualization; one-line diagram; pattern matching; power system visualization; situational awareness; visual analytics;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2011.2119499
Filename :
5733386
Link To Document :
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