Situational Awareness in SCADA/GMS/EMS/DMS: Are you minimizing your risk by having the most real-time information at your fingertips?
- Jun 24, 2011
- Feng Xu
Have you seen the movie “Unstoppable?” It’s about an unmanned, runaway freight train carrying toxic explosive chemicals at 60 miles per hour, and headed straight towards the heart of Scranton, PA. The Traction SCADA system is monitoring the train’s movement and the Chief Dispatcher uses the data to manipulate other trains in the vicinity, moving them away from the main line. Without giving any more details and ruining the movie, it’s important to note that If the dispatcher had enough tools to track everything that was going on, the disaster could have been stopped quickly.
On April 12th 2011, there was a similar real life event with the SCADA system used to monitor and control the main rail lines in Sydney, Australia. The failure of a signal box triggered the loss of communication and control of multiple points, routes, and signals, and resulted in loss of control of six rail lines through Sydney’s main business district. Ultimately, there were 847 train delays and 240 cancellations, stranding over 100,000 people, as it took almost 10 hours to completely restore communications. The problem was initially attributed to a computer glitch, but the root cause investigation revealed that the control system inadequately detected and managed the failure of a network switch, significantly increasing the duration of the outage.
The simple definition of situational awareness is “knowing what’s going on around you” with the objective of preventing abnormal situations.  Lack of situational awareness has been found to be one of the key causes of several blackouts around the world, including the 2003 blackout in the US and the 2006 blackout in the Continental European Electricity Grid.  The February rolling blackouts in ERCOT this year is another example where better situational awareness may have helped predict the extreme cold weather, load peak, and generation shortage which led to the blackouts.
In the control room environment, most operators’ view of what’s happening is limited by the “system” they are using. The common practice of GMS/EMS/DMS vendors is to display a large amount of data without much consideration for the human element. Important information is not easy to find and critical alarms are sometimes missed in “flood” of stale and nuisance messages, resulting in very little awareness of what’s really going on.
Two tools that are effective for achieving good situational awareness are data visualization and alarm processing. The general idea in the use of situational awareness tools is to keep an operators’ attention focused on critical information, make sure they can understand it, and to keep the big picture always available. An effective data visualization and alarming strategy includes:
1)Â Â making data more informational by putting it in context to reference values (e.g. limits, past data, expected value)
2)Â Â using color schemes to make important data stand out, to group data by source, or to represent the status (e.g. normal range, warning, violation)
3)Â Â using graphical tools such as bars graphs and trends to give operator perspective and reduce their memory load.
4)Â Â configuring alarming parameters based on company strategy:
- category – to associate common events that may occur to a point
- class- to define alarm/event tracking in database and how to present alarms on the screen
- priority – to determine the level of importance of the alarm
5)Â Â Alarms should have an operator action and the action should be prioritized.
Two key issues in the EMS Situational Awareness is the quality of the data being received and the model currently being used to analyze the data. Maintenance procedures should be in place to ensure the model is accurate and up to date, and suspect telemetry data is filtered out or minimized. This gives confidence to the users that the information they are viewing is accurate and allows them to make timely decisions in maintaining the power system. Having the most advanced situational awareness tools is worthless if the data being displayed is not accurate.
Some situational awareness tools for EMS include: Voltage contouring; Flow (MVA/AMP) contouring; Phase angle difference contouring;Â flowgate contouring; reactive reserve for each busbar (shown using graphs); violations caused by contingencies; dynamic coloring in one-lines; dashboards to show the overall network state summary.
As opposed to most generation and transmission assets, the components of a distribution network are concentrated in heavily populated areas, and the quantity of elements is significantly higher. The result is much more data to interpret, and many more events and alarms to manage. Data analytics in DMS is a useful tool to filter through all of these alarms and events. Smart Grid analytics combined with data warehousing tools can provide almost infinite combinations of data filters to operators. Therefore, automated analysis of the data must be performed rather.  Utilities are now slowly introducing situational awareness tools in distribution networks from various vendors to provide Smart Grid analytics tools and dashboards.
In summary, problems generally arise because operators do not have a full picture of what is going on with a system until a situation has already occurred. The use of appropriate data visualization tools and alarming strategies create good situational awareness by alerting a user when operational parameters are approaching a violation condition, not just after the violation has already occurred. It is important to remember, however, that situational awareness requirements vary among entities due to different roles in the marketplace, compliance standards, market rules, and customized user preferences.
Michael Kraatz, Rodrigo Lagunes, and Vijayasekar Rajsekar contributed to this article.