Envisioning grid vulnerabilities: multi-dimensional visualization for electrical grid planning

ABSTRACT

Electrical grid planning aims at optimizing the grid through the control of the performance and placement of electrical assets in order to minimize failures or vulnerabilities. With this purpose, grid planners carry out an initial stage of data exploration using a large volume of incident and equipment data collected over extensive time periods. In current practice these tasks are performed manually, which makes it very difficult to recognize patterns and gain insights into the data. In this paper, we propose a parallel multivariate visualization technique as a suitable approach for improving the existing practice. Based on the usage of an interactive visualization tool called BarExam, we demonstrate the feasibility of this visualization technique for displaying the dataset and present example insights that this visualization technique can provide to grid planners.

References

1. Abdullah, K., Lee, C. P., Conti, G., Copeland, J. A. and Stasko, J. 2005. IDS rainStorm: visualizing IDS alarms. IEEE Workshop on Visualization for Computer Security 2005 VizSEC 05 1--10.
2. Axelsson, S. 2003. Visualisation for Intrusion Detection: Hooking the Worm. Proceedings of the 8th European Symposium on Research in Computer Security (ESORICS 2003). Gjovik, Norway, Springer-Verlag.
3. Ball, R., Fink, G., and North, C. 2004. Home-Centric Visualization of Network Traffic for Security Administration. Proceedings of the 2004 ACM Workshop on Visualization and Data Mining for Computer Security Washington, DC, USA, ACM Press.
4. Chiaradonna, S., Giandomenico, F. and Lollini, P. Evaluation of Critical Infrastructures: Challenges and Viable Approaches. Architecting Dependable Systems V, Rogério Lemos, Felicita Giandomenico, Cristina Gacek, Henry Muccini, and Marlon Vieira (Eds.). Lecture Notes In Computer Science, Vol. 5135. Springer-Verlag, Berlin, Heidelberg 52--77. 2008.
5. Colombe, J., Stephens, G. 2004. Statistical Profiling and Visualization for Detection of Malicious Insider Attacks on Computer Networks. Proceedings of the 2004 ACM Workshop on Visualization and Data Mining for Computer Security. Washington, DC, USA, ACM Press.
6. Debar, H., Dacier, M., and Wespi. A. 1999. Towards a Taxonomy of Intrusion-Detection Systems. Computer Networks, 31(8):805--822.
7. Endsley, M. R., Bolté, B., and Jones, D. G. Designing for Situation Awareness.Design 30--34 (Taylor & Francis: 2003)
8. Erbacher, R. F., Garber, M. 2004. Fusion and Summarization of Behavior for Intrusion Detection Visualization. Proceedings of the IASTED International Converence On Visualization, Imaging, and Image Processing. Marbella, Spain
9. Greitzer, F. L., Dauenhauer, P. M., Wierks, T. and Podmore, R. 2009. Human Factors Evaluation of Advanced Electric Power Grid Visualization Tools. Retrieved February 16, 2012, from Pacific Northwest National Laboratory: http://www.pnl.gov/coginformatics/media/pdf/EIOviz-greitzer-4-30_18386.pdf
10. Kosara, R. 2010. Parallel Coordinates. Retrieved February 16, 2012: http://eagereyes.org/techniques/parallel-coordinates
11. Mikkelsen, C., Johansson, J., and Rissanen, M. 2011. Interactive Information Visualization for Sensemaking in Power Grid Supervisory Systems. In Proceedings of the 2011 15th International Conference on Information Visualisation (IV '11). IEEE Computer Society, Washington, DC, USA, 119--126.
12. Mitsubishi Electrics Research Laboratory. Retrieved February 16, 2012: http://www.merl.com/
13. Muelder, C., Ma, K., Bartoletti, T. 2005. A Visualization Methodology for Characterization of Network Scans. Workshop on Visualization for Computer Security (VizSEC 2005)
14. Overbye, T. J., Weber, J. D. 2000. Visualization of power system data. In Proceedings of the 33rd Annual International Conference on System Sciences.
15. Symantec Global Internet Security Threat Report, 2010. Retrieved February 16, 2012, from Symantec Enterprise Security: http://eval.symantec.com/mktginfo/enterprise/white_papers/b-whitepaper_internet_security_threat_report_xv_04-2010.en-us.pdf
16. Wong, P. C., Schneider, K., Mackey, P., Foote, H., Chin, G., Guttromson, R., and Thomas, J. 2009. A novel visualization technique for electric power grid analytics. IEEE Transactions on Visualization and Computer Graphics 15, 410--423
17. Wittenburg, K., Lanning, T., Heinrichs, M., and Stanton, M. 2001. Parallel bargrams for consumer-based information exploration and choice. Proceedings of the 14th annual ACM symposium on User interface software and technology (UIST '01). ACM, New York, NY, USA, 51--60.
18. Wittenburg, K., Malizia, A., Lupo, L., and Pekhteryev, G. 2012. Visualizing Set-Valued Attributes in Parallel with Equal-Height Histograms. Proceedings of Advanced Visual Interfaces (AVI). Capri, Italy. ACM Press.

Index Terms

• Human-centered computing