The world’s energy distribution grids are challenged. Aging infrastructure, increased maintenance and labor costs, and extended restoration times after unplanned outages stoke growing consumer distrust. Energy companies need help, and analytics leader SAS lends them a hand with SAS® Grid Guardian AI, a first-of-its-kind solution that improves reliability while reducing crew injuries and fatalities without adding new equipment. The new solution makes its debut at DISTRIBUTECH International.
“Utilities have a blind spot when it comes to predicting overhead equipment failure and prioritizing predictive maintenance, even if they currently have an APM application and processes in place,” said John Villali, Director of IDC Energy Insights. “Leveraging innovative roaming sensor networks and analyzing pre-failure radio frequency (RF) emissions using AI and machine learning enables utilities to detect degraded overhead equipment and better understand the types of equipment failures most likely to occur. Combined with readily-available circuit-level data, RF emission-based monitoring enables utilities to effectively prioritize maintenance plans for enhanced safety, reliability and uptime.”
Randolph EMC, a rural North Carolina energy cooperative, uses SAS Grid Guardian AI to get ahead of aging overhead equipment failures so the distribution grid remains stable for its members. “It also helps employees detect problems without taking unnecessary risks in the field or adding new equipment to the grid,” said Dennis Mabe, Vice President of Engineering and Operations at Randolph EMC. “Making data-driven decisions that improve service to our members is our goal. SAS helps us gain new visibility into previously unavailable data. With these insights we can plan and prioritize critical repairs to eliminate failures.”
SAS Grid Guardian AI reduces costs, protects workers, improves reliability
SAS Grid Guardian AI analyzes the data flowing from mobile edge computing sensors mounted to utility and service vehicles – like garbage trucks – roaming up and down alleys and streets. The sensors read the RF emissions data, and it’s analyzed with AI and machine learning. The result is energy companies better understand when failures might occur and can more effectively prioritize maintenance schedules.
SAS Grid Guardian AI offers software and services that:
- Reduce injury rates by 38%.
- Identify degraded overhead equipment without added sensors.
- Reduce crew overtime costs by 33%.
- Improve distribution reliability by 18%.
And SAS Grid Guardian AI does all this without adding more equipment to the grid itself.
“SAS Grid Guardian AI combines unprecedented continuous distribution grid equipment condition assessment and the power of AI to enable predictive and prescriptive grid management,” said John L. Lauletta, CEO of Exacter. “This is a breakthrough in grid reliability and resilience.”
Exacter President Geoffrey Bibo added, “Our sensing technology coupled with SAS analytics and insights brings a new level of predictive grid management to utility reliability efforts.”
“Restoring consumer confidence in the reliability of the distribution grid is critical, and a big part of restoring that confidence comes from strengthening the infrastructure,” said Jason Mann, SAS Vice President of IoT. “Experts point to RF emissions as a significant early predictor of future overhead equipment failures. SAS Grid Guardian AI, which could pay for itself in less than a year, combines advanced analytics and AI with innovative mobile IoT sensing technology to prioritize overhead equipment repairs to maintain grid efficiency.”
