Real-Time Data Retrieval and New Visualization Techniques for the Energy Industry

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Real-Time Data Retrieval and New Visualization Techniques for the Energy Industry Raymond P. Klump Lewis University and PowerWorld Corporation Urbana, IL 61801 USA ray@powerworld.

1 Real-Time Data Retrieval and New Visualization Techniques for the Energy Industry Raymond P. Klump Lewis University and PowerWorld Corporation Urbana, IL USA Abstract Effective power system operation requires power system engineers and operators to analyze vast amounts of information. The authors have developed several techniques for visualizing large amounts of data including contouring, animated flows, and 3D visualization. These techniques have been completely integrated into PowerWorld Simulator, an off-line system study tool for use in the energy industry. Integrating these visualization techniques with real-time data sources, such as those available in energy control centers, however, has presented a separate challenge to the wide dissemination of these visualization abilities. This paper presents a case study of integrating these abilities with control centers that utilize the Plant Information (PI) System for data storage and archival. Projects have been completed that integrate these visualization techniques into control centers for Commonwealth Edison in Lombard, Illinois and City Water Light & Power in Springfield, Illinois. A separate pilot project has also been completed with the Tennessee Valley Authority. 1. Introduction Several new visualization techniques have been developed by the authors and their colleagues over the past several years to help power system engineers and others involved with transmission system systems better and more quickly understand their systems. These visualization techniques have been fully integrated into PowerWorld Simulator [1], an off-line transmission system analysis package. Several papers have been written on this topic [2]-[4]. While this work has been very successful, it has limited the application of these visualization techniques to the off-line study environment. This paper summarizes the results of several recent projects which James D. Weber PowerWorld Corporation Urbana, IL USA weber@powerworld.com have taken the visualization techniques from the off-line environment to the real-time world. Three projects have been completed at this time. Projects with CWLP in Springfield, Illinois, and Commonwealth Edison in Lombard, Illinois, have integrated the visualizations with a real-time data base used in the control centers of these two utilities. The third project with the Tennessee Valley Authority was more limited in scope, but has successfully proven the concept. 2. Visualization techniques Prior to discussing the case studies, this section will briefly cover the various power system visualization techniques that have been developed in the previous work by the authors [2]-[4] Animated arrows Animated arrows are used to provide an intuitive understanding of the flow of power in a transmission system network. An example is shown in Figure 1 below. Figure 1 Animated line flow arrows /02 $17.00 (c) 2002 IEEE 1

The size, orientation, and speed of the arrows indicate the direction and magnitude of the power flow on the transmission lines.

2. Dynamically sized pie charts Dynamically sized pie charts are used to assess to location and magnitude of line overloads at a glance.

While this could be done by sorting in a spreadsheet, one would look lose the geographic relevance of the overloads. This technique is demonstrated in Figure 2.

2 The size, orientation, and speed of the arrows indicate the direction and magnitude of the power flow on the transmission lines. This technique is invaluable for providing an immediate understanding of transmission systems to a new engineer, or for presenting transmission system issues to non-technical audiences Dynamically sized pie charts Dynamically sized pie charts are used to assess to location and magnitude of line overloads at a glance. The percentage fill of the pie charts illustrates how close the transmission line is to overload. This allows one to analyze tens of thousands of data points very quickly. While this could be done by sorting in a spreadsheet, one would look lose the geographic relevance of the overloads. This technique is demonstrated in Figure 2. Figure 3 Contouring of system security data Figure 4 shows a contour of price information across a hypothetical market in the Northeastern United States. Note that dynamically sized pie charts can be used in conjunction with the contour data to show other relevant data. The pie charts show transmission lines which are constraining the power market, resulting in the price variations seen. Figure 2 Highlighting flows using pie charts Pie chart visualization is useful, until a large number of them begin to appear simultaneously. When this occurs, contouring is a more useful approach Contouring Contouring is used to represent spatially distributed data. The equal-temperature contours in a newspaper weather report are a common example. Contouring can be used to analyze system security information as well as power market information. Figure 3 shows the transmission system impact of transfers into the Midwest on two transmission system devices. Any transfers from shaded areas on the left of the figure will result in 5% or more of the transfer flowing across the Eau Claire to Arpin transmission line in Wisconsin, while any transfers from shaded areas on the right of the figure would result in 5% or more of the transfer flowing across the Kammer transformer in Ohio. Figure 4 Contouring of system pricing data 2.4. Three-dimensional visualization Three-dimensional visualization has proven helpful when trying to visualize the interrelationships of several pieces of data simultaneously. The visualizations developed build off the existing two-dimensional one-line diagrams used in power systems. Those concerned with power systems are familiar with this environment, making the jump to three-dimensions easier. The third dimension gives us another dimension to visualize data in. The contour image in Figure 5 shows the transmission system impact of a transfer from Wisconsin to Florida. The three-dimensional cylinders show transmission lines with high loadings. The interaction of these two pieces of data can now be better assessed /02 $17.00 (c) 2002 IEEE 2

Figure 5 Contouring of PTDF data with 3D visualization of high line loadings Another example of three-dimensional visualization is shown in Figure 6.

done through the PI-API, an application programming interface for the PI System. In order to supplement this information, data can also simultaneously extracted from flat text data sources.

We call these data the Associated Points. The software must allow the user to specify these points. The Simulator Retriever display that allows the user to define this points is shown in Figure 7.

3 Figure 5 Contouring of PTDF data with 3D visualization of high line loadings Another example of three-dimensional visualization is shown in Figure 6. The contour shows the available transfer capability of areas trying the send power to Northern Illinois, while the cylinders show the magnitude of generation reserves in the respective areas. done through the PI-API, an application programming interface for the PI System. In order to supplement this information, data can also simultaneously extracted from flat text data sources. After defining the data sources, particular pieces of data must then be defined within the visualization software as being associated with data in the PI System. We call these data the Associated Points. The software must allow the user to specify these points. The Simulator Retriever display that allows the user to define this points is shown in Figure 7. Figure 6 ATC Contouring with 3D visualization of generation reserves 3. Data retrieval methods The development of visualization techniques for power systems has been very successful. These techniques have been integrated into PowerWorld Simulator. This however has limited the use of the visualization techniques to this off-line study tool. When moving the graphical capabilities over to a realtime system, the issue of retrieving the data must be addressed. Data retrieval in a control center often means retrieving information from a variety of sources, so the software must be set up to handle this. In the examples presented in this paper, new software, called Simulator Retriever, communicates directly with a PI System. PI System stands for Plant Information System, and is a real-time database and data archival system sold by OSI Software. The communication with the PI System was Figure 7 Defining Data Sources and Points Once the data sources and points are defined, the software must then map this information to an object on the graphical diagram. The authors refer to this process as creating aliases. After setting up the appropriate data sources, points, and creating the aliases, the graphics can be updated by pulling data from the data sources. With the mechanism for retrieving data defined, the software can then be setup to query all registered data sources for new data at regular user-specified intervals, thus providing a near real-time visualization of the information. In addition to querying registered data sources automatically at preset intervals, Simulator Retriever can retrieve information on demand. With the click of a button, the user can command Simulator Retriever to retrieve new data from registered information sources. Many data sources provide the additional capability of storing archival data. The PI System provides such abilities through its PI-DataArchive. Within Retriever, one can retrieve data from an instant in the past. It also allows one to retrieve data over a time window in the past. In the latter case, the user supplies the start and end /02 $17.00 (c) 2002 IEEE 3

4 times that define the window and the size of the time intervals to study during the window. The software retrieves data at each interval and displays it to animate for the user how the system changes over time. Setting this up is done through the dialog shown in Figure 8. Figure 9 shows the model of CWLP s system prior to data retrieval, while Figure 10 shows the system after the data has been populated from the PI System. Figure 9 CWLP system prior to data retrieval Figure 8 Control panel for Simulator Retriever If a large enough set of data is retrieved so that a power flow model can be reasonable defined, it is also possible to set up software which retrieves real-time data, and then switch over to the off-line environment to perform power flow analysis or other study tasks. 4. Case studies Several case studies have been completed to demonstrate the viability of retrieving data in the manner presented. The first project was completed for City Water Light & Power (CWLP) in Springfield, Illinois. In this project, a full power flow model was created which could be used in an off-line study environment. This model could then be populated with real-time data directly from CWLP s PI System, providing a real-time visualization of the information in their energy management system. Using the capabilities of the PI- DataArchive, historical data could be viewed as well. These capabilities of this allowed those within the control center to utilize all the advanced visualization capabilities. In addition to this, anyone person within CWLP who had access rights to the PI System could view the real-time control center data from their own desktop computer. This included those at remote business offices, or those at the Dallman generating station, CWLP s largest station and location of its newest gas turbine generator. The remote viewing of real-time data was an ability that CWLP never had before as well. Figure 10 CWLP system after data retrieval Another project has been completed with the Commonwealth Edison Control Center in Lombard, IL. Recently, ComEd had reconfigured their control center, with part of this entailing the purchase and installation of a complex computer projection system. This system allows ComEd to project computer images on a two by six array of screens. This computer projection system was vastly underutilized because of their inability to display useful information in this new environment. ComEd was interested in making use of this new environment and approached PowerWorld about putting in some simple displays for them initially. In particular, ComEd was interested in viewing the status of their phase-shifters which control the flow of power into downtown Chicago. The data source for this task was again an existing PI System. Again Simulator Retriever was developed to integrate directly with this data source, and visualizations can now be viewed directly on the computer projection system in their control center /02 $17.00 (c) 2002 IEEE 4

The PowerWorld project was completed successfully.

Figure 13 A three-dimensional display for TVA Figure 11 ComEd s Control Center with New Display Figure 12 Closeup of Simulator Retriever displays Finally, a pilot project has been completed to prove

At this time, the data source for this pilot project has been through flat text files, however the results have been very successful.

5 The PowerWorld project was completed successfully. Figure 11 and Figure 12 show scanned photographs of Simulator Retriever displays in the computer projection system in Commonwealth Edison s control center. Figure 13 A three-dimensional display for TVA Figure 11 ComEd s Control Center with New Display Figure 12 Closeup of Simulator Retriever displays Finally, a pilot project has been completed to prove the concept of integrating real-time data with these new visualization techniques at the Tennessee Valley Authority control center in Chattanooga, Tennessee. At this time, the data source for this pilot project has been through flat text files, however the results have been very successful. Future projects to more thoroughly integrate the visualizations with the real-time system are underway. Figure 13 and Figure 14 show displays taken directly from the real-time data in TVA s control center. Figure 14 Screen shot showing a voltage contour of the TVA transmission system 5. Conclusion Analyzing the large amount of data related to the electric power system is a challenge. Visualization techniques have proven to be of great use in studying systems in an off-line environment. The projects discussed in the paper have shown that this success can be transferred to the visualization of real-time data in control centers. 6. References [1] PowerWorld Simulator, PowerWorld Corporation Website, [2] T.J. Overbye, J.D. Weber, Visualizing the electric grid, IEEE Spectrum, Volume 38, Issue 2, Feb. 2001, pp [3] T.J. Overbye, J.D. Weber, New methods for the visualization of electric power system information, IEEE /02 $17.00 (c) 2002 IEEE 5

6 Symposium on Information Visualization 2000, InfoVis 2000, pp c. [4] J.D. Weber, T.J. Overbye, Voltage contours for power system visualization, IEEE Transactions on Power Systems, Volume 15, Issue 1, Feb. 2000, pp /02 $17.00 (c) 2002 IEEE 6

Visualization of Power System Data

Visualization of Power System Data Thomas J. Overbye overbye@ece.uiuc.edu University of Illinois at Urbana-Champaign Urbana, IL 61801 USA Jamie D. Weber weber@powerworld.com PowerWorld Corporation Urbana,