Visualization Techniques in Smart Grid


Visualization is an established methodology in scientific computing. It has been used in many fields because of its strong capability in large data management and information display. However, its applications in power systems, especially in Smart Grid are still in infancy stage. Besides, while there were a lot of researches working on visualizing data in transmission power system, the study on displaying distribution power system data was limited. Therefore, in this paper, author proposed some techniques to visualize the Smart Grid data at distribution. They are classified in three categories, which are low dimensional techniques, multivariate high dimensional techniques and Geographical Information System (GIS) techniques.

Share and Cite:

D. Nga, O. See, D. Quang, C. Xuen and L. Chee, "Visualization Techniques in Smart Grid," Smart Grid and Renewable Energy, Vol. 3 No. 3, 2012, pp. 175-185. doi: 10.4236/sgre.2012.33025.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] M. Bernasocchi, “Visualizing Multivariate Spatial-Temporal Data,” M.Sc. Thesis, University of Zurich, Zurich, 2011.
[2] H. L. Jin and H. J. Liu, “Research on Visualization Techniques in Data Mining,” International Conference on Computational Intelligence and Software Engineering, Wuhan, 11-13 December 2009, pp. 1-3. doi:10.1109/CISE.2009.5366364
[3] D. A. Keim, “Visual Exploration of Large Data Sets,” Communications of the ACM, Vol. 44, No. 8, 2001, pp. 38-44. doi:10.1145/381641.381656
[4] D. A. Keim, “Information Visualization and Visual Data Mining,” IEEE Transactions on Visualization and Computer Graphics, Vol. 8, No. 1, 2002, pp. 1-8. doi:10.1109/2945.981847
[5] M. C. F. de Oliveira and H. Levkowitz, “From Visual Data Exploration to Visual Data Mining: A Survey,” IEEE Transactions on Visualization and Computer Graphics, Vol. 9, No. 3, 2003, pp. 378-394. doi:10.1109/TVCG.2003.1207445
[6] T. J. Overbye and J. D. Weber, “Visualization of Power System Data,” Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Maui, 4-7 January 2000, p. 7. doi:10.1109/HICSS.2000.926744
[7] J. D. Weber and T. J. Overbye, “Voltage Contour for Power System Visualization,” IEEE Transactions on Power Systems, Vol. 15, No. 1, pp. 404-409. doi:10.1109/59.852151
[8] T. J. Overbye, “Power System Visualization,” Automation of Electric Power Systems, Vol. 29, No. 16, 2005.
[9] T. J. Overbye, A. P. Meliopoulos, D. A. Wiegmann and G. J. Cokkinides, “Visualization of Power Systems and Components,” Power Systems Engineering Research Center, Ithaca, 2005.
[10] T. J. Overbye and J. D. Weber, “New Methods for Visualization of Electric Power System Information,” IEEE Symposium on Information Visualization, Salt Lake City, 9-10 October 2000, pp. 131-136.
[11] T. J. Overbye and D. A. Wiegmann, “Reducing the Risk of Major Blackouts through Improved Power System Visualization,” 15th Power System Computation Conference, Liege, 22-26 August 2005, 8 p.
[12] T. J. Overbye, “The Role of Power System Visualization in Enhancing Power System Security,” In: S. C. Savulescu, Ed., Real-Time Stability in Power Systems: Techniques for Early Detection of the Risk of Blackout, Springer, New York, 2005, pp. 293-314.
[13] T. J. Overbye, “Transmission System Visualization for the Smart Grid,” Power Systems Conference and Exposition, Atlanta, 15-18 March 2009, pp. 1-2.
[14] R. Klump, D. Schooley and T. Overbye, “An Advanced Visualization Platform for Real-Time Simulations,” 14th Power System Computation Conference, Sevilla, 24-28 June 2002, 8 p.
[15] T. J. Overbye, E. M. Rantanen and S. Judd, “Electric Power Control Center Visualization Using Geographic Data Views,” Bulk Power System Dynamics and Control—VII. Revitalizing Operational Reliability, 2007 iREP Symposium, Charleston, 19-24 August 2007, pp. 1-8. doi:10.1109/TVCG.2008.197
[16] P. C. Wong, K. Schneider, P. Mackey, H. Foote, G. Chin, R. Guttromson and J. Thomas, “A Novel Visualization Technique for Electric Power Grid Analytics,” IEEE Transactions on Visualization and Computer Graphics, Vol. 15, No. 3, 2009, pp. 410-423.
[17] AREVA T & D Energy Management Systems, 2008. Available from:
[18] Y. Sun and T. J. Overbye, “Visualization for Power System Contingency Analysis Data,” IEEE Transactions on Power Systems, Vol. 19, No. 4, 2004, pp. 1859-1866. doi:10.1109/TPWRS.2004.836193
[19] E. Boardman, “The Role of Integrated Distribution Management Systems in Smart Grid Implementations,” Power and Energy Society General Meeting, Minneapolis, 25-29 July 2010, pp. 1-6.
[20] Y. X. Cai and M.-Y. Chow, “Exploratory Analysis of Massive Data for Distribution Fault Diagnosis in Smart Grids,” Power & Energy Society General Meeting, Calgary, 26-30 July 2009, pp. 1-6. doi:10.1109/PES.2009.5275689
[21] H. Tram, “Technical and Operation Considerations in Using Smart Metering for Outage Management,” Transmission and Distribution Conference and Exposition, Chicago, 21-24 April 2008, pp. 1-3. doi:10.1109/TDC.2008.4517273
[22] J. Triplett, S. Rinell and J. Foote, “Evaluating Distribution System Losses Using Data from Deployed AMI and GIS Systems,” Rural Electric Power Conference, Orlando, 16-19 May 2010, pp. C1-C8. doi:10.1109/REPCON.2010.5476204
[23] D. Y. R. Nagesh, J. V. V. Krishna and S. S. Tulasiram, “A Real-Time Architecture for Smart Energy Management,” Innovative Smart Grid Technologies, Gaithersburg, 19-21 January 2010, pp. 1-4.
[24] S. Nunoo and A. K. Ofei, “Distribution Automation (DA) Using Supervisory Control and Data Acquisition (SCADA) with Advanced Metering Infrastructure (AMI),” 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply, Waltham, 27-29 September 2010, pp. 454-458. doi:10.1109/CITRES.2010.5619797
[25] D. J. Maguire, M. Batty and M. F. Goodchild, “GIS, Spatial Analysis, and Modelling,” ESRI Press, Redlands, 2005.
[26] T. Sutton, O. Dassau and M. Sutton, “A Gentle Introduction to GIS,” Chief Directorate: Spatial Planning & Information, Eastern Cape, 2009.
[28] P. Compieta, S. Di Martino, M. Bertolotto, F. Ferrucci and T. Kechadi, “Exploratory Spatio-Temporal Data Mining and Visualization,” Journal of Visual Languages & Computing, Vol. 18, No. 3, 2007, pp. 255-279. doi:10.1016/j.jvlc.2007.02.006
[29] M. Weber, M. Alexa and W. Muller, “Visualizing TimeSeries on Spirals,” 2001 IEEE Symposium on Information Visualization, San Diego, 22-23 October 2001, pp. 7-13. doi:10.1109/INFVIS.2001.963273
[30] A. Kjellin, L. W. Pettersson, S. Seipel and M. Lind, “Evaluating 2D and 3D Visualizations of Spatiotemporal Information,” ACM Transactions on Applied Perception, Vol. 7, No. 3, 2010, Article ID: 19.
[31] X. Li and M.-J. Kraak, “New Views on Multivariable Spatiotemporal Data: The Space Time Cube Expanded,” International Symposium on Spatio-Temporal Modeling, Spatial Reasoning, Analysis, Data Mining and Data Fusion, Vol. 36, 2005, pp. 199-201.
[32] C. Tominski, P. Schulze-Wollgast and H. Schumann, “3D Information Visualization for Time Dependent Data on Maps,” Proceedings of the 9th International Conference Information Visualization, Cambridge, 6-8 July 2005, pp. 175-181. doi:10.1109/IV.2005.3

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.