Case Study

How Satellites and AI Helped a Fortune 500 Electric Utility Achieve Its Lowest Vegetation CI Levels Ever


The utility beat its reliability targets by a third despite flat utility vegetation management budgets

Lowest vegetation CI levels in company history
Increased system SAIFI by 30% despite flat budget
Over 90% alignment with satellite predictions


Company: Fortune 500 utility
Location: Southeastern USA
Solution: AiDash Intelligent Vegetation Management System (IVMS)

Everything has a natural cycle. Vegetation grows and abates, and budgets rise and fall. The challenge for vegetation managers is that these cycles rarely coincide. Trees continue to grow even when budgets wither.

One Fortune 500 energy company felt the pain especially hard in 2019 when its utility vegetation management budget remained at 2018 levels and vegetation-related customer interruptions (CI) rose to almost 7 figures. Caught between Nature and Finance, they succeeded by taking a new perspective and shifting to the view from space.

A Fresh Perspective From Above

Satellite perspective

In 2019, the company turned to AiDash’s satellite-powered vegetation management systems. These systems apply recent advancements in satellite imagery, artificial intelligence, predictive algorithms, machine-learning, and more to assess the state of vegetation along an electric utility’s rights of way, recommending and prioritizing vegetation issues.

In 2020 and 2021, the company beat its vegetation SAIFI goals every month and lowered their vegetation CI rate one-third. In fact, they reached their best overall CI levels ever. Their experts found that the AiDash systems had a major impact on grow-in related outages.

But what allowed them to achieve these historic results? Rethinking their utility vegetation management approach and turning to innovation for better information. They had formidable challenges to overcome because budgets remained low, and costs were increasing.

These issues compounded with the size of the Fortune 500 electric utility’s territory: millions of customers, 100,000 miles of overhead distribution, more than 1,000 contractors, and an annual vegetation management budget near $100 million.



Costs Rise Sky High

Those historic results were far from easy to achieve. The trim modeling tool showed a high deficit between the miles needed to be cut and the miles they could afford to. By 2022, they had a $22 million funding gap between actual trimming and the planned, natural trim cycle.

Why was that? Cost increases. In the last 10 years, their average cost to trim a mile of line increased 100%. Despite negotiating bid packages for more favorable rates, 2022 costs still increased 24% over the previous year. In that environment, they had to carefully select the most impactful feeders to avoid losing their recent reliability gains.



Down-to-Earth Insights

That’s where AiDash’s cycle optimization software offered significant advantages. With information about every feeder in the Fortune 500 electric utility’s system, it looked at criticality, customers, vegetation load, effort, and outage histories. Then it ranked the feeders based on what needed trimming according to natural trim cycles, and what trimming they could afford within existing budgets. This new data-driven approach allowed the company to prioritize work on the highest ranked feeders that would lead to the best results for their customers.

Vegetation managers are delighted that the tool helps them identify the natural cycle of every feeder in the system – and not one is the same as another. The analysis evaluates the feeders, using the company’s unique parameters. For example, it triggers when 20% of a line is within two feet of the conductor and alerts the team to trim that feeder in the next year. It looks at the feeder and network levels and rolls up to a region then to the operating company. The cycle trim tool aligns with over 90% accuracy to their field validations based on work type, density, and clearances.

Another crucial tool for the company’s vegetation management is AiDash’s Uniform Trim Plan module. With almost 100 people on their vegetation team, trim plans used to come in a wide variety of formats. Now, within the tool itself, they send in uniform plans to supervisors, discuss what actions to push out or pull into the plans, generate final plans, and send them out to contractors for bids.

A current project with the Fortune 500 utility’s vegetation team and AiDash is to include more than 25 years of historical growth information with current data and use artificial intelligence to replace field estimates with precise insights. The decades of information about species composition, growth rates of the species by region, and clearances in rural and urban settings, feeds into a model of the entire 100,000-mile system. Once completed, the model will allow the vegetation team to use real-time insights to recalibrate their prediction modeling and reduce the human error in their current system.

The electric utility has also found that added feeder segmentation is vital for managing price increases. With almost 200 feeders of 100 miles or more in length, they found the AiDash optimization module especially useful and have segmented over 30 feeders already. One of their feeders, over 200 miles long, which was prohibitively expense to trim all at once at $5,000 to $6,000 per mile. But with satellite analysis, they were able to identify four different segments that had their own trim cycles, ranging from 5 to 7 years. All they had to do was keep up-to-date GIS information in the AiDash system, which did the analysis for them. They expect more opportunities to segment feeders as their vegetation environment evolves.

Another advantage of this capability is that the AiDash system keeps the history of all the feeders and their segments. If turnover or a promotion takes an experienced manager out of a role, their replacement now has every bit of the Fortune 500 utility’s feeder history – even current maps – in the system itself. They just need to log into the system and start work.

Despite credible efforts to eliminate emergencies through ongoing maintenance, there will always be exceptions: hazard trees. The company uses the Hazard Tree Spotter app that AI Dash created for them and has logged more than 25,000 trees. The app allows any contractor with a smartphone to report overhangs, leaners, and other hazards. Those are added to the backlog and if too many accumulate, the company has the data to take to their regulators to request and justify more funding. Then they can use the system to assign trees to vendors and generate correct work orders.

By finding and proactively managing its vegetation grow-ins, this electric utility has dramatically reduced its vegetation outages. When crews go out to fix vegetation outages, there’s always an unexpected cost that magnifies over the year. The Fortune 500 utility has reduced their normal range of more than 20,000 outages per year by about 5,000. Not only does that improve their system reliability but it avoids the expense of repairs.

Storm damage

Storms wreak havoc on vegetation just as they do on built structures. What does a vegetation team do if their careful trimming plan becomes obsolete because a storm takes down much of the vegetation they had targeted? This Fortune 500 electric utility experienced a major storm that damaged tens of thousands of poles, but they were ready to respond. They used the AiDash platform to true up their models to show the actual vegetation that remained along each feeder after the storm. It calculated all new vegetation profiles, growth cycles, and locations of reconstructed feeders. Then it revised the trim cycles to match the new model so that the company could recover and resume operations as quickly as possible.

A Clear View of LiDAR and Satellites

Satellite and LiDAR

These vegetation management professionals evaluate and use a wide variety of tools and technologies to help them become more efficient and effective at delivering power to their customers. They use satellite-powered vegetation management and LiDAR and find both offer valuable information that they’ve used in bid packages. However, they see drawbacks in LiDAR because it supplies a one-time image while satellite technology gives them frequent updates and current information. At more than $100 per mile, LiDAR scans would be tens of millions of dollars, making LiDAR imaging too expensive to conduct regularly.



Making Space for Innovation

All these successes began when top executives saw the impact of vegetation issues on the Fortune 500 utility’s reliability. Facing troubling CI figures and limited budget flexibility, those executives encouraged their vegetation managers to “think outside of the box.” Having already optimized the traditional vegetation management procedures, the vegetation managers saw little potential in doing more of the same. So, they stepped outside their comfort zone and looked at innovations in remote sensing technology and artificial intelligence coming from AiDash.

Did it work for them? Their results tell the story. They beat their reliability (Vegetation SAIFI) targets by a third and achieved their lowest vegetation CI levels ever despite flat vegetation management budgets.

What’s Next?

As satellites improve their capabilities in multispectral imagery, this Fortune 500 electric utility will soon explore tree health modeling with AiDash. Outages are not always caused by growing vegetation. When diseased trees fall unexpectedly onto lines, they incur repair costs of thousands of dollars each and directly affect customer service. By monitoring the health of nearby trees, the electric utility expects important gains in reliability.

Want to see how satellites and AI can help transform grid resiliency at your utility? Get a demo today!