In the US, a Detroit grid modernisation project has found that adding sensors on the line near existing switching locations is most effective at isolating problems.
The pilot between Detroit-based utility DTE Energy and smart grid solutions provider Tollgrade reports that the proximity of sensors to switching hardware allows utility lineman to go directly to a nearby switch, open it and isolate the problem area.
The findings were published this week in a Predictive Grid Quarterly report, which provides nine months of sensor data, the third in a series of eight over the next two years.
The document produced by Tollgrade also found that based on 12 months of sensor data collected from DTE Energy and other utilities, 84% of events captured by the company’s smart grid platform LightHouse were line disturbances.
The document states: “The trending analysis over the past twelve months shows that the pattern of line disturbances and outages are closely related, giving more proof that monitoring line disturbances as a precursor to outages should become an industry standard.”
And as found in previous reports, most events occur in the summer months then drop off dramatically in October, with a slight uptick in the winter during the months of November and December.
The data also shows a large spike in events of all types in March due to several ice storms that impacted a large section of North America.
Detroit grid modernisation platform
The study, which falls under the umbrella of a Clinton Global Initiative, uses a grid platform consisting of medium-voltage smart grid sensors that are battery free and operate on cellular or Wi-Fi communication spectrums.
The other part of the LightHouse platform is Predictive Grid analytics software that communicates with sensors to bring back all of the captured events.
The project, which started in June 2014, is located in the Detroit metropolitan area, the heartland of the US automobile industry, where any loss of power directly affects the country’s GDP.
Power outages cost US businesses US$15,709 every 30 minutes according to data from Tollgrade.