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Eyeing demand growth, ERCOT calls for energy investments across Texas

ERCOT now estimates an extra 40,000 megawatts of growth in demand for electricity by 2030 compared with last year’s outlook. Photo via Getty Images

With the Electric Reliability Council of Texas forecasting a big spike in demand for electricity over the next five to seven years, the operator of Texas’ massive power grid is embracing changes that it says will yield a “tremendous opportunity” for energy investments across the state.

The council, known as ERCOT, now estimates an extra 40,000 megawatts of growth in demand for electricity by 2030 compared with last year’s outlook. According to ERCOT data, 40,000 megawatts of electricity would power roughly 8 million Texas homes during peak demand.

ERCOT has been under intense scrutiny in the wake of recent summertime and wintertime debacles involving power emergencies or outages. The organization manages 90 percent of Texas’ power supply.

“As a result of Texas’ continued strong economic growth, new load is being added to the ERCOT system faster and in greater amounts than ever before,” Pablo Vegas, president and CEO of ERCOT, says in a news release. “As we develop and implement the tools provided by the prior two [legislative sessions], ERCOT is positioned to better plan for and meet the needs of our incredibly fast-growing state.”

Meeting the increased demand will create opportunities for energy investments in Texas, says ERCOT. These opportunities will undoubtedly lie in traditional energy production as well as in renewable energy segments such as solar, wind, and “green” hydrogen.

Some of the opportunities might be financed, at least in part, by the newly established Texas Energy Fund. The fund, which has been allotted $5 billion for 2025-26, will provide loans and grants for construction, maintenance, modernization, and operation of power-generating facilities in Texas.

ERCOT is also working with partners to develop tools aimed at improving grid reliability and market efficiency.

ERCOT says changes in its operations that’ll be required to fulfill heightened demand for power will position the nonprofit organization “as a significant component of the economic engine driving the national economy.”

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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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