Eaton Announces Breakthrough, AI-Powered Innovation to Help Utilities Strengthen Wildfire Prevention Efforts

• Lab simulations and testing demonstrate highly accurate, fast fault detection technology designed for grid-edge implementation on utility distribution lines
• Collaboration among Eaton, U.S. Army Corps of Engineers (USACE) Engineer Research Development Center (ERDC), National Renewable Energy Laboratory and North American utilities drives novel solution
• Eaton to present on wildfire mitigation technologies at the 2025 DistribuTECH and TechAdvantage industry conferences

Intelligent power management company Eaton today announced a groundbreaking innovation strengthening wildfire prevention efforts on utility distribution systems. Achieved in collaboration with the U.S. Army Corps of Engineers (USACE) research and development arm, the U.S. Army Engineer Research and Development Center (ERDC), the National Renewable Energy Laboratory (NREL) and multiple North American utilities, the new Eaton HiZ Protect^™ solution addresses a long-standing challenge for electric utilities: accurately and quickly detecting and mitigating high-impedance (HiZ) powerline faults that could potentially ignite wildfires. Pilot projects with multiple North American utilities are underway to further refine the technology, which is expected to be first available in Eaton's Form 7 recloser controls.

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Eaton delivers breakthrough innovation to help utilities strengthen wildfire prevention efforts with grid-edge controls and intelligent fault detection. Photo credit: Dennis Schroeder, NREL.

Existing grid protection technologies struggle to accurately prevent or identify HiZ faults, prompting utilities to resort to public safety power shutoffs during high-risk conditions. Eaton's HiZ Protect technology will help strengthen utility wildfire prevention efforts by automatically and accurately identifying and isolating these powerline faults. Under lab-simulated conditions and using real-world grid data from multiple utilities, the Eaton technology detected and de-energized HiZ faults with greater than 90% accuracy.

"Fortifying the electric grid against the threat of wildfires has never been more important and at Eaton, we're helping the industry accelerate these efforts through our expansive solutions and research and development efforts," said Chris Herbst, PhD, Eaton's vice president of strategic partnerships and innovation. "We work with most utilities across North America and know wildfire prevention efforts are a top priority. In collaboration with USACE ERDC, NREL and multiple U.S. utilities, we're breaking the boundaries of what electrical systems can do to help protect communities and the environment."

HiZ faults, often caused by fallen trees or damaged insulators, are historically difficult to detect due to their low fault current levels and unique characteristics. Eaton's approach to identifying and mitigating high-impedance faults incorporates three novel elements including, integrated sensors, machine learning and edge-based implementation. The solution can be deployed in grid-edge monitoring and control devices such as Eaton's Form-7 recloser controls to provide high-fidelity data. This capability is critical in remote areas, where communication infrastructure is limited and the ability to rapidly respond to grid conditions is essential.

"It is critically important be able to identify fault situations and take action to de-energize impacted power lines and curtail risk of wildfire to protect people and property, including military and utility systems," said Nathan Peterson, electrical engineer at the USACE ERDC Construction Engineering Research Laboratory (CERL). "We believe Eaton research, development and commercialization of high impedance fault detection technology offers immense opportunity to fortify the grid by quickly and reliably delivering the data needed to improve wildfire detection and mitigation at the grid edge."

The Eaton solution was developed through extensive research on the unique fault signatures of high-impedance events on the grid and precise measurement of variables such as tree species, soil types and environmental conditions. Hundreds of simulations and field experiments were conducted at Eaton's Thomas A. Edison Test Center in Franksville, Wisconsin. Eaton used the data to develop a novel machine learning algorithm capable of reliably predicting and reducing the potential for these powerline faults to initiate wildfires. Today, the company is piloting the technology with utilities and across various geographic conditions to further refine and validate the technology.

During the 2025 DistribuTECH conference in March 2025, Souvik Chandra, PhD, a senior specialist engineer at Eaton's Research Labs, will participate in a panel discussion on the strategies utilities are deploying to mitigate wildfire risks, including Eaton's novel fault detection technology.

Learn more about Eaton's approach to wildfire mitigation and read the white paper on harnessing artificial intelligence for high impedance fault detection and mitigation.

Eaton is an intelligent power management company dedicated to protecting the environment and improving the quality of life for people everywhere. We make products for the data center, utility, industrial, commercial, machine building, residential, aerospace and mobility markets. We are guided by our commitment to do business right, to operate sustainably and to help our customers manage power ─ today and well into the future. By capitalizing on the global growth trends of electrification and digitalization, we're helping to solve the world's most urgent power management challenges and building a more sustainable society for people today and generations to come.

Founded in 1911, Eaton has continuously evolved to meet the changing and expanding needs of our stakeholders. With revenues of nearly $25 billion in 2024, the company serves customers in more than 160 countries. For more information, visit www.eaton.com. Follow us on LinkedIn.

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Kristin Somers

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Regina Parundik

Cobblestone Communications

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