The objective of this project was to demonstrate a new data visualization technology for those applications where process graphics are inadequate, due to the quantity and geographical distribution of measurement data. We selected a relevant, real-world application, i.e. monitoring renewable energy facilities spread throughout the U.S., for this demonstration. Large applications, such as electrical grids, pipelines, wind farms, even distributed retail outlets with potentially millions of data points, are candidates for this technology. The key is to selectively enable/disable the presentation of aggregated and actual data, based on zoom level, to avoid overloading the operator with too much data.
Here are the highlights:
- Displays real-time plant data superimposed on top of Microsoft Bing Maps (Virtual Earth)
- Allows a utility to monitor its wind farms across the U.S. using MS Bing Maps (Virtual Earth) images
- Shows actual windmill power output from the OSI Software PI Historian, when zoomed in to the lowest level that shows the physical windmills within the farm
- Displays aggregate data from the PI Historian that shows wind farm power output, power output for the state, and power output for the U.S. at higher zoom levels
- Versions for SharePoint Server and standard IIS web site
- Incorporates off-the-shelf ComponentOne Silverlight Maps component and map slices to associate data and display widgets to zoom levels
- Developed in Microsoft C#
Demonstration of Silverlight Virtual Earth Web Part by Nimble Solutions and Todd Schick of ComponentOne (hi res screencast)
Demonstration of Silverlight Virtual Earth Web Part by Nimble Solutions and Todd Schick of ComponentOne (low res screencast)
Sample Silverlight Virtual Earth Maps Web Part Screen Shots Within SharePoint
A. This example uses eight wind farms in the U.S. owned by a mythical utility, NUGreen Energy. Here, the aggregated output for the U.S. and the three wind states, California, Texas, and Iowa, are fetched from the PI historian and shown at a low zoom level. The gauges and bar charts of the display widgets show the actual values, and the grid data can be shown on drill down (see the Lone Star flag of Texas).
B. The user can pan and zoom using standard Virtual Earth features. But, a pop-up window at the right allows quick navigation to individual wind farms, in this case Cajon Pass in California.
C. At the highest zoom level, live data for each wind mill is retrieved from the PI historian and super-imposed on the map. Note the clarity of the wind mills and their shadows. A click on the gauge of the display widget will show a detailed gauge display showing the aggregate or individual information along with the target value so the key performance indicator (KPI) can be easily seen. In this case, the aggregate production of the Cajon Wind Farm is below target (needle is in the red zone).
D. At the next lower zoom level, the individual windmill data are hidden leaving only the aggregate Cajon Pass wind farm data to be seen. To be shown, data must have its coordinates (latitude and longitude) within the viewing box, but also have the zoom level of the web part match or exceed the zoom level for the data in the SQL database.
E. In California, wind farms tend to be in the mountain passes. In Texas, wind farms are often installed along the perimeter of a mesa, as can be seen in the map of the Pecos River wind ranch in Texas.
F. The user can use the pop-up panel on the right to see the data for state wind production. Here, the three wind farms are shown in California, along with the aggregate California wind information. A click on the bar chart of the state display widget (with the golden bear) shows actual and target production data for the state from PI in vertical bar chart format.
G. At the lowest zoom level, only aggregate wind generation information from the U.S. is shown. Obviously, all the aggregate and individual data in the system are within the view box, but are designated in the database to be shown at higher zoom levels than shown here.
