As power outages go, the iguana affair was a mundane one. On July 27, a hapless lizard shorted a piece of electrical equipment in the middle of the Florida Keys and knocked out power for 11,000 local residents. It was an act of nature no outage prevention system would have been able to predict. But since the lizard climbed inside a substation, repair crews were able to locate the short and restore power in 10 minutes. “Spotting problems within the limited space of a substation is relatively easy,” says Chris Prince, application engineer at GE Digital Energy. “It’s a high-density nerve center for distributing power. But good luck finding and fixing a problem that fast when it happens along the miles of overhead and underground lines connecting the substation to the consumers.”
In an era when a smartphone can quickly pinpoint its location on a map, few power providers know that customers lost electricity before somebody calls them. Fewer still can see whether the outage was caused by a fallen tree branch, a lightning or faulty equipment.
Americans are taking notice. A new survey measuring public perception of grid resiliency found that many respondents were willing to pay $10 per month on top of their electricity bill to make sure that the grid becomes more reliable (see the results here).
The survey, which was commissioned by GE’s Digital Energy business, also found that a majority wanted utilities to start using digital communications and social media tools to keep them informed in real time during a power outage. “Consumers want to see investment in technology that prevents power outages and reduces the time it takes to turn power back on,” says John McDonald, director of technical strategy and policy development at GE Digital Energy.
Utilities are getting the message. As wireless networks became more ubiquitous, power companies started placing digital sensors along its lines and inside switches, breakers, smart meters and other devices. The sensors feed grid data to data collection centers where algorithms process it to create a virtual map of the distribution network.
Prince says that the network map resembles a tree where the transmission lines that come from the power generation plants are the roots and the substation is the trunk. “The feeder circuits that reach out through neighborhoods to residential customers are the branches where we’ve traditionally had the least visibility,” he says.
Prince says that an outage event could be due to a single cause or multiple causes nested together. This makes the prime cause harder to find. But digital systems that connect the grid to the Industrial Internet and string together smart sensors, controls, and software can quickly detect and locate trouble, and then isolate a likely problem area along the right branch. “Instead of telling the crew to patrol miles of a line, I can narrow the location to a block or two,” he says. “At the same time, the control system will quickly restore power to the other lines leading from the trunk that did not suffer any damage, and bring power back to those customers sooner.”
McDonald says that a number of utilities have already started implementing automation on the feeder lines where they see the most value. NSTAR, for example, brings electricity to 1.1 million customers living in central and eastern Massachusetts. Starting in 2009, the company reached out to GE and started building a “self-healing” grid. Today the system consists of 2,000 smart switches and 5,000 voltage and current sensors. The system was already tested by Hurricane Irene in 2011 and Hurricane Sandy in 2012.
During Irene, 500,000 customers lost power but the system was able to reroute it and turn the lights back on for close to half of them within an hour. NSTAR calculates that the new grid visibility has allowed it avoid 600,000 customer outages so far. “The concept of grid monitoring has been around for decades,” McDonald says. “But the advances in big data, software, fiber optics and digital wireless communications now really bring it alive.”
Not even lizards can stop it.
Filed Under: M2M (machine to machine)