When a disaster is an opportunity
In an emergency, when every second is critical, gathering data for future reference isn't typically a high priority. The primary mission of responders is to get the power flowing again- and fast.
But with the rise of powerful analytical tools, data gathered during incidents and outages is increasingly valuable. Rich data on incidents can help engineers understand problems and better respond to them. Machine learning algorithms can comb through incident data for patterns, and use those patterns to predict impending situations, identify the most vulnerable equipment, and prioritize limited resources.
Data is valuable, but for its value to be realized, it needs to be gathered and organized in a way that's usable. Gathering data in real time without relying on time-consuming manual processes is becoming easier thanks to the rising ubiquity and falling cost of sensors that stream information in real time. Organizing all that data is a more challenging task. To transform data into actionable analysis, it needs to be gathered in a single source of truth and put in the right context.
For San Diego Gas and Electric, making intelligent use of data during incidents has been transformative - not only for situational awareness during an incident, but for incident re-creation and “playback” after the fact. SDG&E uses the PI System, integrated with GIS software and real-time weather data, to monitor and gather data from thousands of devices in the field, keep that data in context, and generate automatic notifications that go to the right people when situations arise.
A rich archive of incident data that can be easily accessed and analyzed is a tremendous asset to a power utility. When operators can identify at a glance the situations in which incidents typically occur - which seasons, under which weather conditions, in which places, or with what kind of impacts on assets - they can plan ahead, prioritize mitigation approaches, and craft intelligent strategies for response deployment.
To learn more, see our paper: “Real-time data for Incidents: Transforming incident management in the utility industry.”