ECE 530 – Analysis Techniques for Large-Scale Electrical Systems

1. ECE 530 – Analysis Techniques for Large-Scale Electrical Systems Lecture 27: Power System Visualization Prof. Tom Overbye Dept. of Electrical and Computer Engineering University of Illinois at Urbana-Champaign overbye@illinois.edu

2. Announcements • HW 9 should be done before the exam but need not be turned in • Final Wed. Dec 18 from 1:30 to 4:30pm in EL 260 • Closed book, closed notes; you may bring in one new note sheet and your exam 1 note sheet, along with simple calculators • Design length is no longer than the midterm

3. Intro to Power System Visualization For thousands of years humans have used visual forms to convey information; computers have greatly facilitated the speed of making displays. Power system visualization is a subset of the information visualization field: How can visual representations be used to aid understanding of abstract data. The need is driven by data overwhelm, but the desired task is the key driver.

4. Brief History of Power System Visualization: The Early Years Commonwealth EdisonControl Room Circa 1920 Utility Control Room, 1960’s Source: W. Stagg, M. Adibi, M. Laughton, J.E. Van Ness, A.J. Wood, “Thirty Years of Power Industry Computer Applications,” IEEE Computer Applications in Power, April 1994, pp. 43-49

5. 1980’s: Character-Based EMSs By the 1980’snumerous utilities hadEMSs with large numbersof character-based displays.In addition to SCADA, networkanalysis applications werebeing used. PSE&G Control Center in 1988 Source: J.N. Wrubel, R. Hoffman, “The New Energy Management System at PSE&G,” IEEE Computer Applications in Power, July 1988, pp. 12-15.

6. Full Graphics With Viewports Started Appearing in Late 1980’s Full Graphic “Windows” Security Analysis Severity Summary K. Ghoshal, L.D. Douglas, “GUI Display Guidelines Drive Winning SCADA Projects,” April 1994 A. Thiyagarajah, B. Carlson, J. Bann, M. Mirheydar, S. Mokhtari, “Seeing Results in a Full Graphics Environment,” July 1993

7. Early Combination of Text and Graphics on Onelines Madison Gasand ElectricControl Room, Cerca 1991. Note the graphical view of the MGE systemon the right monitor (anda youngerDon Morrow!)

8. 1990’s: PC-Based University Research IEEE 118 Bus OperatingState Visualization Pseudo-GIS Control AreaDisplay H. Mitsui and R.D. Christie, “visualizing Voltage Profiles for Large Scale Power Systems,” IEEE Computer Applications in Power, July 1997, pp. 32-37 T.J. Overbye, G. Gross, M.J. Laufenberg and P.W. Sauer, “Visualizing Power System Operations in the Restructured Environment”, January 1997. T.J. Overbye, P.W. Sauer, C.M. Marzinzik, and G. Gross, “A User-Friendly Simulation Program for Teaching Power System Operations,” IEEE Transactions on Power Systems, pp. 1725-1733, November, 1995.

9. Late 1990’s: Contouring, 3D, Multiple Control Areas (Wide Area) By the late 1990’s computer hardware/software had advanced sufficiently to allow for interactive, wide-area power system displays covering multiple control areas, including color contouring and 3D. Projection type displays were beginning to appear in utility control centers, gradually displacing the static map boards.

10. Color Contouring Voltage Magnitude Contour Bus LMP Contour R.D. Christie, P.M. Mahadev, Visualizing Power System Data, EPRI Report TR-102984, April, 1994. J.D. Weber and T. J. Overbye, "Power system visualization through contour plots," 29th North American Power Symposium, Laramie, WY, pp. 457-463, October 1997. J.D. Weber and T. J. Overbye, "Voltage contours for power system visualization," IEEE Trans. on Power Systems, vol. PWRS-15, pp. 404-409, February, 2000.

11. Early 3D Visualizations Early 3D View of BusVoltage Magnitudes 3D View of PTDFs andLine Constraints F. L. Alvarado, Y. Hu, C. Rinzin, and R. Adapa, “Visualization of Spatially Differentiated Security Margins,” Proc. 11th Power Systems Computation Conference (PSCC), Avignon, France, August, 1993. T.J. Overbye, J. D. Weber and M. J. Laufenberg, "Visualization of flows and transfer capability in electric networks," Proc. 13th Power Systems Computation Conference (PSCC), Trondheim, Norway, pp. 420-426, June 1999. T. J. Overbye, J. D. Weber, "New Methods for the Visualization of Electric Power System Information," Proc. IEEE Symposium on Information Visualization 2000, Salt Lake City, UT, October 2000, pp. 131-136c.

12. Multiple Control Area Visualizations 3D ATC and Generation Reserves Visualization of Inter-ControlArea PTDF Values

13. Commonwealth Edison Control Center, 2001 By the early 2000’s video projection systems were starting to be used in utility control rooms. Some utilities still prefer static (tile)map boards

14. 2009 Control Room: MISO Photo Source: MISO

15. 2009 Control Room: ISO New England Photo Source: ISO New England

16. Visualization Technology Assessment • The overall purpose of power system visualizations is twofold: • They should enhance human capabilities (e.g., we are very good at recognizing patterns) • They should alleviate their limitations (e.g., we are very slow [relative to computers] at performing simple arithmetic) • Key driver for human factors assessment is the task at hand.

17. A Visualization Caution Source: E. Tufte, The Visual Display of Quantitative Information, Graphics Press, Cheshire, CT, 1983. Just because information can be shown graphically, doesn’t mean it should be shown. Three useful design criteria from 1994 EPRI visualization report: 1) natural encoding of information,2) task specific graphics, 3) nogratuitous graphics

18. Human Factor Testing Caution T.J. Overbye, D.A. Wiegmann, A.M. Rich, and Y. Sun, "Human factors aspects of power system voltage contour visualizations," IEEE Transactions on Power Systems, pp. 76-82, February 2003. There is actually very little in the human factors literature with regard to power system visualizations. Doing formal human factors experiments is quite time consuming, and ultimately of somewhat limited value in determining the usefulness of visualizations in a control center setting.

19. Understanding the Entire Process is Key • Understanding the entire processes in which the visualizations are embedded is key. • What is the “information access” cost? • How will the information be used and shared? • Is it raw data, or derived values? • Should the visualizations sit on top of a model, or is a standalone process sufficient? • Ultimately, what are the desired tasks that need to be accomplished?

20. Normal, Emergency and Restorative Control States • Power systems operate in three very different states: normal (> 99% of time), emergency and restorative. Visualizations should be optimized for the particular state. • Potential blackouts can have vastly different time scales, from seconds (e.g., 8/14/03 in NY) to days (e.g., hurricanes) • Many blackouts have time scales of minutes to hours, allowing the potential for operator intervention.

21. True GIS vs. Pseudo-GIS Displays • Power system visualizations have traditionally been done using a “pseudo-GIS” (one-line diagram) approach. • There is a growing trend towards integrating power system information into true GIS visualizations. • Usefulness depends on application. For some applications, like fault location, they can be useful, but there can be significant shortcomings

22. True GIS vs. Pseudo-GIS True GIS Example Two Pseudo-GIS Examples Satellite background can camouflage data; also interesting electric data occursin a small geographic area

23. Contouring of Power System Information Contouring power system information originally was thought to have three problems: 1) electric distance was not necessarily related to geographic distance, 2) electric data was not globally defined, 3) electric devices like LTC transformers introduced discrete changes in values. Research/experience has shown all issues can be addressed; contouring is strongly recommended, but color mappings are important.

24. Contouring Color Perception • However, care needs to be taken with color. • Human have three distinct color receptors (cones – rods are used for low light), with blue being hard to see • Only a small number of colors can be accurately differentiated Source: Information Visualization by Colin Ware, Fig 4.2

25. Contouring Examples Examples show the same data using either a continuous, fullrange color mapping (left) or a discrete, full range color mapping (right). Partial range color mappings can also be used to highlight information (e.g., buses with voltages above/belowspecified limit values).

26. Animation and Motion The human factor literature indicates that selective use of animation can quite effective for rapidly drawing attention and conveying information. However, animation must be used with care since too much can result in distraction; motion should also have a natural encoding (like flow on a transmission line).

27. Three Dimensional (3D) Visualization Results on 3D are mixed. Advantages: 1) useful for showing relationships between multiple variables, 2) our brains are designed for interacting with 3D (i.e., we live in a 3D world), 3) increasing common and fast interface. Disadvantages: 1) perceptual ambiguities of depth, size and distance occur, 2) objects in foreground can obscure those in background, 3) can induce vertigo on large screens.

28. 3D Examples

29. PMU Visualization • Phasor measurement units (PMUs) return power system voltages, currents, and powers at rates up to 30Hz. • Visualization focus has tended to be on direct visualization of bus voltage angles. • The direct usefulness of angles is still an area of active research • From a visualization perspective the current techniques to show this information are 1) contouring, 2) numerics, 3) gauges/pie charts

30. PMU Visualization Examples

31. Display of Time-Varying Information Seeing how data is changing is an important visualization challenge. Strip charts are a common approach. Trying to display multiple data values in a geographic context is difficult.

32. Power Grid Analytics • Analytics is defined (by Wikipedia) as the discovery and communication of meaningful patterns in data. • Several terms are used to denote the idea of discovering insight from data: • Statistics (by far the oldest), data mining, knowledge discovery, data analytics • Analytics are applied to determine interesting patterns, which can then be visualized

33. Transient Stability Results Example

34. Display Maintenance and Standardization Keeping displays up-to-date is a continuing challenge; displays that can’t be easily maintained will eventually not be used. Currently very little standardization exists in power system visualizations. Standardization must balance individual/company preferences with the need to quickly and accurately convey information between different entities.

35. Future Directions for Visualization • Power system visualization is rapidly changing from just a focus of how data/information is shown on the screen, to how to extract information from the growing tidal wave of data • Data mining algorithms will be of growing importance • “Model-based” visualizations will be required • Data will need to be shared throughout organizations (e.g., breaking down walls between operations/planning, transmission/distribution)