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Hear from two leading utilities, Duke Energy and Exelon Utilities how they are changing the vegetation management process using advanced analytics. Vegetation management – is perhaps the costliest preventative maintenance measure for electric utilities. Despite its importance, most utilities across the industry still manage vegetation the same way today as they did decades ago.
At Exelon Utilities they are evaluating how existing utility data and publicly available satellite imagery can be leveraged at scale to reduce vegetation management costs and improve reliability performance. By using analytics to identify overlap of vegetation management work, unnecessary routine expenditures can be avoided to reduce costs. Improved vegetation risk models can also mitigate the number of vegetation outages. They are leveraging available data sources – such as high-resolution satellite imagery, historical outage data, maintenance records, and GIS data.
The Duke Energy team is building an enterprise wide AI work planning, analysis and scheduling system to support their Transmission vegetation management operations. The system will use AI to predict risk at the span level by work type (e.g. hazard tree, trimming, herbicide, mowing, etc.). Risk scores, along with cost unitization and work value model output, will be used to create optimized work plans and schedules that minimize risk and cost while optimizing system reliability and crew productivity. Additionally, a Scenario Planning tool will utilize the AI models to evaluate and predict vegetation management performance through the running of various “what-if” scenarios.
Feel free to ask questions in the discussion forum below - speakers will be responding as quickly as they can. View this webinar by the end of the day on June 10 and get entered to win a $100 Amazon Gift Card.
What does blowout risk mean?
Blowout risk is related to the movement of the conductors due to wind.
This was a fantastic session from Duke and Exelon- Steve, what has the reaction of the workforce been to this new approach? Also, what has the reaction of the workforce been to this new approach?
So far, the reaction has been positive. While the system, as expected, has needed training and adjustment, the initial results have been good and that has helped to build confidence in what we’re doing.
Have you been able to update GIS errors with the satellite data?
One of our satellite data providers, were able to use AI to identify poles locations using high resolution satellite, so there are definitely opportunities. We are working actively with the GIS data quality team to understand how our findings might influence their program.
So many great points from Duke Energ and Exelon. Will definitely recommned this presentation to my colleagues that work in Vegetation management.
Thank you Makeba!
Roughly, what is the cost of the collective system (acquisition and implementation)? Are you managing costs reductions to offset these cost?
Unfortunately, I’m not at liberty to divulge that for Duke Energy, but we do expect the benefits to offset the development and deployment costs and deliver on-going value.
This was a really interesting, and informative session. Well presented and clear. I really enjoyed it. Thanks a lot sharing. According to you what is the most difficult part in these projects ? data acquisition ? modeling ? or change management ?
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