NV5 Geospatial’s distribution network data shows pole usage. (Image: Nv5 Geospatial)
Asset and vegetation management applications help utilities minimize risk and improve the reliability of electric distribution networks
Geospatial data firm NV5 Geospatial is applying remote-sensing data analysis to improve the way utilities manage their distribution networks. The company mapped more than 5.5 million miles of utility distribution networks in the United States using a combination of lidar and orthoimagery sensors on mobile and airborne platforms to acquire data for both asset and vegetation management.
Analysis of this geospatial data enables electric utilities to minimize risk and maximize reliability, while increasing efficiency.
“An aging grid, workforce shortages, increasing energy demands and an uptick in major weather events are combining to create a perfect storm that could impact reliability, customer service and safety for electric utilities across the country,” said Eric Merten, vice president, Commercial Group at NV5 Geospatial. “A boots-on-the-ground approach to management cannot keep up with demands related to aging equipment, compliance, pole loading and vegetation encroaching on infrastructure.
“NV5 Geospatial’s innovative remote-sensing applications and data analysis tools give utilities the power to proactively address problems in their distribution network before they impact operations or customers,” Merten said.
A distribution network (purple) and vegetation risks (red/yellow pins). (Image: NV5 Geospatial)
Built on the success of its remote-sensing applications for utility transmission networks, NV5 Geospatial’s distribution management solutions offer end-to-end capabilities — from acquiring accurate, high-quality geospatial data to data analysis and visualization using custom viewers and enterprise geospatial information systems (GIS) — and can be customized to meet the use cases and budgets of utility companies.
Using NV5 Geospatial’s tools, distribution network asset managers can achieve compliance with National Electrical Safety Code (NESC) clearance guidelines, and get clear visibility into joint use of poles to prevent pirating.
The NV5 Geospatial remote-sensing data also can help quantify vegetation with distribution rights-of-way and determine risk based on proximity to wires and poles.
How AI and machine learning algorithms redefine the way utility companies manage their infrastructure
By Jaro Uljanovs, Lead AI Developer and Data Scientist, Sharper Shape
Artificial intelligence (AI) boasts a wide range of potential applications, across nearly every industry imaginable — healthcare, automotive, retail, even fast food. But it’s the utility industry where AI and machine learning (ML) are beginning to demonstrate some of their most impactful effects on many aspects of the business. Power companies are increasingly leaning on AI to improve their electricity delivery and prevent potential wildfires, and AI is actually enhancing, rather than eliminating, human jobs.
From data collection and analysis to their presentation of actionable insights, AI and ML algorithms are quickly redefining how utility companies manage their electric infrastructure.
Consolidating and classifying data
Utility companies oversee massive infrastructure networks, comprising poles, conductors, substations and transmission and distribution lines that span thousands of miles. The vegetation surrounding this key infrastructure must also be monitored, as it presents a danger of fire or outage.
Taking a comprehensive snapshot of these assets means utilizing a variety of different sensors for network inspections. These sensors include lidar, color (RGB), hyperspectral and thermal imagery.
This allows the system to capture everything — from vegetation proximity, to infrastructure assets, to individual components (such as insulators on poles) and their operational integrity, to hot spots indicating potential fire risks.
That’s a lot of data to capture, catalog and process. And there are a lot of individual elements within that data — even in just one image — to pinpoint and classify, let alone do so accurately. Classifying billions of data points across all of those images is an impossibly time-consuming task to do manually.
Photo: shaunl/E+/Getty Images
AI and ML tools can accomplish that same work — scanning thousands of images collected across thousands of miles of utility infrastructure — in seconds. Lidar point cloud segmentation can detect conductors (quite a difficult component-type to segment) with an accuracy of over 90%, while hyperspectral image segmentation can identify vegetation species with an accuracy of up to 99%.
More than that, when paired with drone sensors, these algorithms can also improve the upfront collection of images and data. AI and ML tools help to adjust sensor positioning in real time, in the event a signal is lost or the drone veers slightly away from its inspection flight path.
By helping to readjust the sensors’ bearings while in flight, AI not only ensures more accurate data collection, but also that the flight doesn’t need to be done again or prematurely ended because of faulty data collection, saving time and money. AI pinpoints any faults in the sensors or the drone’s flight path while in the air, recalibrating as needed and identifying individual elements within the data as it comes through the sensor’s video feed.
Breaking down silos to create a holistic data approach
Key to all of this is eliminating the silos that tend to naturally build up between different data segments. In the utility inspection space, asset management, vegetation management, different sensors and so on all produce their own disparate, walled-off sets of data.
When data is kept siloed like this, it becomes unnecessarily difficult if not impossible for teams to derive companywide insights or conclusions from the information being collected. And what good is all that data if it can’t be used to check against itself and enhance other sets of data?
Good data management can’t exist in a piecemeal approach. It needs to be holistic, and AI provides the impetus to make that happen. AI provides a central resource for pooling all these data sources together, making it easier to cross-analyze for potential problems — like wildfire-prone vegetation or damaged components. When these issues are collected in one system, it becomes much easier to identify faults and resolve them — and do so far faster than it would be to manually sift through countless images of poles or vegetation maps.
And for all the stereotypical concerns about AI eliminating work for human beings, at utility companies AI actually enhances the role that people have to play in the network inspection process. Because the AI is what analyzes the data, it’s not something that is dependent on the potentially biased expertise of a professional human inspector, nor is it prone to fatigue and the anomalous results that can come from that. But at the same time, AI can’t do everything itself. It’s a tool for presenting clearer, more accurate and more actionable information for the people to then act on with their own judgment.
There’s a lot of easy-to-make assumptions, both good and bad, about AI. But at the end of the day, what AI really means for the utility industry is a more efficient and effective tool for providing the right information about a power company’s infrastructure — its transmission and distributions lines, its poles, and its nearby vegetation — into the hands of its key decision makers.
Sharper Shape, a provider of unmanned aerial utility inspection solutions, has released the Heliscope 2.0, an onboard payload system that expands the company’s aerial sensing portfolio into the manned helicopter industry.
According to the company, the Heliscope 2.0 integrates multiple sensor systems into a single, lightweight helicopter payload, capable of simultaneously collecting a range of data types required for utility maintenance and vegetation management inspections.
Deployment of the Heliscope 2.0 enables optimized inspection and maintenance schedules, offering potential cost savings in those operational activities by as much as 50 percent.
The Heliscope 2.0 also stands out with its flexible mounting configurations and ability to adapt for mounting on many different helicopter types.
For example, the system can be mounted on most Bell Jet/Long Ranger helicopters using its FAA-approved nose mount, or attached to numerous other typical helicopter models using its unique Glider aerodynamic sled.
The U.S. Federal Aviation Administration (FAA) permits mounting the Heliscope 2.0 to helicopters by using the cargo hook found on many helicopter models; this user-friendly method is approved by FAA under a classification for gliders.
“While drones are a very flexible and safe method for performing utility inspections, there are situations where manned helicopters are the preferred vehicle to host sensors during certain utility inspections,” said Mikko Saarisalo, Sharper Shape’s vice president of drones and project lead for the Heliscope 2.0 project. “The new Heliscope 2.0 provides a solution for those situations where we need to operate over greater distances or in harsher environments than the drones can easily accommodate. This system takes our data harvesting efficiency and productivity up to a level unprecedented in the industry.”
CORE includes algorithms to automatically analyze lidar point clouds and quickly generate utility vegetation management reports. Further, its unique automatic issue detection (AID) machine vision software uses artificial intelligence (AI) to eliminate the daunting task of performing frame-by-frame image data inspection, allowing personnel to focus on other aspects of inspection compliance.
CORE applications work equally well with either Sharper Shape’s proven unmanned aerial inspection services, or with the new Heliscope 2.0 manned aircraft solution.
“The fact that the Heliscope 2.0 integrates fully with our CORE software suite is a huge benefit,” said Sharper Shape CEO Ilkka Hiidenheimo. “We can collect all the key inspection assets and measurements in one high-speed pass, and then easily pass these files to our CORE suite for automatic processing. Sharper Shape is the only company on the market that offers this range of options for collecting aerial data and for processing this data automatically into a wide range of digital report formats.”
The Heliscope 2.0 system is now available for immediate contract services in the U.S., South America and Europe.
