by the numbers

Report: Texas scores significant chunk of federal clean energy investment

For the 2023 budget year, Texas’ total pot of federal money ranked second behind California’s. Photo via Getty Images

On a per-person basis, Texas grabbed the third-highest share of federal investment in clean energy and transportation during the government’s 2023 budget year, according to a new report.

Texas’ haul — $6.2 billion in federal investments, such as tax credits and grants — from October 1, 2022, to September 30, 2023, worked out to $204 per person, bested only by Wyoming ($369) and New Mexico ($259). That’s according to the latest Clean Investment Monitor report shows. Rhodium Group and MIT’s Center for Energy and Environmental Policy Research produced the report.

For the 2023 budget year, Texas’ total pot of federal money ranked second behind California’s ($7.5 billion), says the report. Nationwide, the federal government’s overall investment in clean energy and transportation reached $34 billion.

Other highlights of the report include:

  • Public and private investment in clean energy and transportation soared to $239 billion in 2023, up 37 percent from the previous year.
  • Overall investment in utility-scale solar power and storage systems climbed to $53 billion in 2023, up more than 50 percent from the previous year.
  • Overall investment in emerging climate technologies (clean energy, sustainable aviation fuel, and carbon capture) during 2023 surpassed investment in wind energy for the first time. This pool of money expanded from $900 million in 2022 to $9.1 billion in 2023.

The Lone Star arm of the pro-environment Sierra Club says the federal Inflation Reduction Act, which took effect in 2022, “includes a dizzying number of programs and tax incentives” for renewable energy.

“While it will take several years for all the programs to be implemented, billions in tax incentives and tax breaks, along with specific programs focused on clean energy development, energy efficiency, onsite solar, and transmission upgrades, means that Texas could help lower costs and transform our electric grid,” says the Sierra Club.

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A View From HETI

Researchers have secured $3.3 million in funding to develop an AI-powered subsurface sensing system aimed at improving the safety and efficiency of underground power line installation. Photo via Getty Images

Researchers from the University of Houston — along with a Hawaiian company — have received $3.3 million in funding to explore artificial intelligence-backed subsurface sensing system for safe and efficient underground power line installation.

Houston's power lines are above ground, but studies show underground power is more reliable. Installing underground power lines is costly and disruptive, but the U.S. Department of Energy, in an effort to find a solution, has put $34 million into its new GOPHURRS program, which stands for Grid Overhaul with Proactive, High-speed Undergrounding for Reliability, Resilience, and Security. The funding has been distributed across 12 projects in 11 states.

“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,” U.S. Secretary of Energy Jennifer M. Granholm says in a DOE press release.

UH and Hawaii-based Oceanit are behind one of the funded projects, entitled “Artificial Intelligence and Unmanned Aerial Vehicle Real-Time Advanced Look-Ahead Subsurface Sensor.”

The researchers are looking a developing a subsurface sensing system for underground power line installation, potentially using machine learning, electromagnetic resistivity well logging, and drone technology to predict and sense obstacles to installation.

Jiefu Chen, associate professor of electrical and computer engineering at UH, is a key collaborator on the project, focused on electromagnetic antennas installed on UAV and HDD drilling string. He's working with Yueqin Huang, assistant professor of information science technology, who leads the geophysical signal processing and Xuqing Wu, associate professor of computer information systems, responsible for integrating machine learning.

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

“If proven successful, our proposed look-ahead subsurface sensing system could significantly reduce the costs of horizontal directional drilling for installing underground utilities,” Chen continues. “Promoting HDD offers environmental advantages over traditional trenching methods and enhances the power grid’s resilience.”

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