The U.S. Department of Energy recently launched an ARPA-E program called Grid Overhaul with Proactive, High-speed Undergrounding for Reliability, Resilience, and Security, or GOPHURRS. The DOE allocated $34 million for 12 projects in 11 states, aimed at modernizing and strengthening the power grid through development of cost-effective, high-speed, safe underground technologies.

“Modernizing our nation’s power grid is essential to building a clean energy future that lowers energy costs for working Americans and strengthens our national security,” said U.S. Secretary of Energy Jennifer M. Granholm in a DOE press release.

Reliance on overhead power lines often leads to widespread outages during extreme weather. Hurricanes like last July’s Beryl, which left 250,000 Texans without electricity for at least a week, expose vulnerabilities in the nation’s aboveground power grid.

The Edison Electric Institute states that underground power lines are 8–10 times more reliable than overhead lines, but less than 20% of U.S. power lines are buried. Reasons include the cost, which can run 5–10 times more than installing overhead lines, and safety issues with underground installation methods (such as trenching, which can damage other buried utilities). Underground installations also extend traffic detours and ground surface disruption. And yet, other countries surpass U.S. underground power line installation, e.g., France (40%), Germany (70%) and the Netherlands (90%).

To address this in part, “Artificial Intelligence and Unmanned Aerial Vehicle Real-Time Advanced Look-Ahead Subsurface Sensor,” one of the selected projects that was awarded $3.3 million in funding, will combine technological expertise from Honolulu-based Oceanit with Tier-One research capabilities of the University of Houston to develop a state-of-the-art subsurface sensing system to guide safe and efficient underground power line installation.

The project’s goal is to create a real-time, high-resolution look-ahead sensing system using unmanned aerial vehicles, electromagnetic resistivity well logging and machine learning to detect underground obstacles in front of a drill bit, minimizing damage to existing infrastructures and enabling a smoother installation process. If successful, the project should result in producing a prototype capable of generating near-real-time, high-resolution underground images during horizontal directional drilling (HDD).

Key collaborator Jiefu Chen, associate professor of electrical and computer engineering at UH, believes this ahead subsurface sensing system could significantly reduce the costs of HDD for installing underground utilities. “Promoting HDD offers environmental advantages over traditional trenching methods and enhances the power grid’s resilience.”

Chen’s focus is to design electromagnetic antennas installed on UAV and HDD drilling string, as well as optimization of the subsurface imaging system. Yueqin Huang, assistant professor of information science technology, leads the geophysical signal processing necessary for constructing precise subsurface images ahead of the drill bit, and Xuqing Wu, associate professor of computer information systems, is integrating machine learning for faster modeling and real-time image generation.

“Advanced subsurface sensing and characterization technologies are essential for the undergrounding of power lines,” Chen said. “This initiative can enhance the grid’s resilience against natural hazards such as wildfires and hurricanes.”