The opportunities are here for utilities.
From customer service to system reliability, innovative technologies can augment and improve manual human processes.
Some innovations are already in place.
On the customer side, smart meters and online customer portals reduce the need for service calls. On the reliability side, LiDAR helps track vegetation growth to prevent service issues.
Now, says Entergy Corporation’s former Vice President of Distribution Services Gary Huntley, let’s add satellites and artificial intelligence (AI).
Satellite-view information and history combined with self-learning or AI can predict vegetation growth. And that means AI can help utilities prescribe precision maintenance to ensure reliable delivery.
Read on to consider the top three takeaways from the podcast featuring Huntley and hosted by Scott MacKenzie. Or listen now.
Watch the full episode
Top three takeaways
Takeaway 1: It’s Tough To “Keep Eyes” on Everything
Technology for utilities has remained standard for many years.
Likewise, the inspection process, using methods that largely involve the field force observing the line miles of the T&D grid, has remained the same.
The challenge is, says Huntley, “If you have 100,000 line miles of wires strung out across the country, it’s really hard for you to put your eyes on every single part of that system.”
So, averages and best estimates are used. Average trim cycles are arranged as budgets allow.
These trim cycles, however, are scheduled without the benefit of information such as weather patterns and unanticipated growth.
Takeaway 2: Clear Assessment Is Vital To Ensure Grid Reliability
A few years back utilities began to move into LiDAR, to collect more granular information regarding vegetation growth.
LiDAR monitoring via aircraft provides a view across the grid. The downside is the cost — and that LiDAR presents a singular instance with no historical comparisons.
LiDAR monitoring via drone is more cost-effective. However, the drone operator in most cases must have a clear line of sight, which can be problematic across some terrains.
Analyzing data from the LiDAR assessment can provide insight into how to prescribe trim and maintenance activities. Yet, there is still a gap as that information does not give historical context or integrate with other data.
Takeaway 3: Get the Full Picture With Satellites and AI
To get the full picture, Huntley advocates adding satellites and AI.
Like LiDAR, satellite imagery provides granular, detailed information, at scale.
Unlike LiDAR, satellites update that information repeatedly, creating a historical record.
The computing power of a satellite and AI solution then evaluates the satellite imagery, weather data, and geographic data, as well as the maintenance budget: In a very short time it will map out a prioritized plan.
“The solution is artificial intelligence, self-learning,” says Huntley. “You update the inputs, and it will update the calculation. It’s amazing.”
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