Geospatial Analysis of Grid Alerts & Warnings
Analyzing grid alerts & warnings geo-spatially. This capability unlocks the possibilities for further producing insights from the data.
The Utility Problem
As electricity distribution grids are becoming more modern, new operational measurement data streams are being created daily by integrating various time series generation devices. This time series data presents a massive potential for insights and situational awareness. One of the adapted techniques is setting the thresholds for which only desired data are highlighted to get these potent data out of the swell of time series. Such thresholds then generate alerts and warnings, which can be analyzed further.
Setting thresholds for displaying the selected variables is very important, as it might indicate possible problems arising in the grid. When alerts and warning data are analyzed, a vital part of the process is often forgotten: proper data visualization. Results in tables are usually less precise than results on a map. For example, geospatial coordinates tell us nothing, or it is complicated to know all the streets in all the cities where a utility operates. Map results also offer a new perspective on the problem. Often, the problem can be solved more quickly since it provides the context of the space and its relation to other geospatial elements. On the map, areas of the cluster of values where a threshold has been exceeded are visible at a glance. It is easier to identify it for further detailed investigation.
Another advantage of geospatial alerts and warnings data becomes apparent when there are many results, as a map chart is much less overcrowded than other charts. While a bar chart with 100 or more marks would be crowded, displaying the same data on a map is very clear, digestible and pleasing to the eye. Of course, map visualizations cannot be used for all results, but they are more suitable for this type of display. Another critical parameter is the level of detail we can perform with the analysis. Analyzing the whole grid without breaking it down into smaller parts is not efficient enough. We need more details to get added value from the data and determine specific action items.
For these reasons, utility professionals need a system to analyze the grid alerts and warnings geospatially. This capability unlocks the possibilities for further producing insights from the data.
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