In Analytics

Large power transformers (LPT) are the workhorses of the North American electric transmission grid, and many have lived past their life expectancy. The U.S. Department of Energy reports that average LPT is 40 years old; 70 percent of LPTs are 25 years or older. These assets are becoming a weak link in the chain of networked transmission assets and may be subject to catastrophic failure, including from severe weather.

If transmission systems fail, large-scale outages can occur. According to a different Department of Energy report, 85 percent of U.S. outages affecting 10,000 customers or more in 2015 were caused by weather or by asset failure. These outages cause customers economic and cost transmission organizations lost revenue and damaged reputation. Regulators are increasingly focused on loss-of-load probability and loss-of-load hours, both key reliability measures.

The Department of Energy also reports that LPTs cost up to $7.5 million dollars each, weigh up to 400 tons, and take up to 18 months to procure and install. The money and time required goes up significantly if new engineering is required. The cost of LPTs accounts for 15-50 percent of total transmission capital expenditures.

For all these reasons, there is an urgent need to understand the operational contingency of heavily loaded LPTs to manage and reduce outages, and to bridge the time until critical LPTs can be replaced.

With analytics you can make the most of what you have while planning for new assets. And with an 18 month delivery cycle, utilities need to start that analysis now.

The growing array of smart, connected devices in the transmission system generates large silos of data. That data can be useful in maintaining safe, reliable, affordable and sustainable transmission operations, but it cannot be correlated, analyzed and applied in a timely manner without advanced visual analytics.

Recently, Siemens and Space-Time Insight announced a partnership in part to tackle the issue of large power transformers.

Situational intelligence provides a number of ways to apply advanced analytics to silos of data for managing the current population of LPTs more effectively. Consider three scenarios:

  • By correlating and analyzing the health of LPTs along identified transmission corridors with demand forecasts and power dispatch schedules, transmission operators are able to prioritize the delivery of power using assets that are relatively healthier than other assets. This helps organizations increase grid reliability and make the most of their current assets.
  • By correlating weather forecasts, LPT health and forecasted energy demand, analytics gives transmission operators advanced warning of weather impacts on transmission assets so that they can respond accordingly to avoid outages and asset damage.
  • By forecasting the impact of removing some LPTs from service, analytics gives transmission planners better insight for planning and executing outages necessary for LPT maintenance, repair and replacement, potentially extending the life of these essential assets.

With the scale of the power grid and past deficit of investment in transmission infrastructure, we will be dealing with aged LPTs for many years. Analytics gives us tools to make the most of the assets we currently have, but it won’t make LPTs immortal.

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