grant funding

Houston researcher wins competitive NSF award for work tying machine learning to the power grid

The UH team is developing ways to use machine learning to ensure that power systems can continue to run efficiently when pulling their energy from wind and solar sources. Photo via Getty Images

An associate professor at the University of Houston received the highly competitive National Science Foundation CAREER Award earlier this month for a proposal focused on integrating renewable resources to improve power grids.

The award grants more than $500,000 to Xingpeng Li, assistant professor of electrical and computer engineering and leader of the Renewable Power Grid Lab at UH, to continue his work on developing ways to use machine learning to ensure that power systems can continue to run efficiently when pulling their energy from wind and solar sources, according to a statement from UH. This work has applications in the events of large disturbances to the grid.

Li explains that currently, power grids run off of converted, stored kinetic energy during grid disturbances.

"For example, when the grid experiences sudden large generation losses or increased electrical loads, the stored kinetic energy immediately converted to electrical energy and addressed the temporary shortfall in generation,” Li said in a statement. “However, as the proportion of wind and solar power increases in the grid, we want to maximize their use since their marginal costs are zero and they provide clean energy. Since we reduce the use of those traditional generators, we also reduce the power system inertia (or stored kinetic energy) substantially.”

Li plans to use machine learning to create more streamlined models that can be implemented into day-ahead scheduling applications that grid operators currently use.

“With the proposed new modeling and computational approaches, we can better manage grids and ensure it can supply continuous quality power to all the consumers," he said.

In addition to supporting Li's research and model creations, the funds will also go toward Li and his team's creation of a free, open-source tool for students from kindergarten up through their graduate studies. They are also developing an “Applied Machine Learning in Power Systems” course. Li says the course will help meet workforce needs.

The CAREER Award recognizes early-career faculty members who “have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization,” according to the NSF. It's given to about 500 researchers each year.

Earlier this year, Rice assistant professor Amanda Marciel was also granted an NSF CAREER Award to continue her research in designing branch elastomers that return to their original shape after being stretched. The research has applications in stretchable electronics and biomimetic tissues.

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A View From HETI

Deloitte predicts AI will represent 57 percent of IT spending by U.S. oil and gas companies in 2029. Photo via Unsplash.

Get ready for a massive increase in the amount of AI spending by oil and gas companies in the Houston area and around the country.

A new report from professional services firm Deloitte predicts AI will represent 57 percent of IT spending by U.S. oil and gas companies in 2029. That’s up from the estimated share of 23 percent in 2025.

According to the analysis, the amount of AI spending in the oil and gas industry will jump from an estimated $4 billion in 2025 to an estimated $13.4 billion in 2029—an increase of 235 percent.

Almost half of AI spending by U.S. oil and gas companies targets process optimization, according to Deloitte’s analysis of data from market research companies IDC and Gartner. “AI-driven analytics adjust drilling parameters and production rates in real time, improving yield and decision-making,” says the Deloitte report.

Other uses for AI in the oil and gas industry cited by Deloitte include:

  • Integrating infrastructure used by shale producers
  • Monitoring pipelines, drilling platforms, refineries, and other assets
  • Upskilling workers through AI-powered platforms
  • Connecting workers on offshore rigs via high-speed, real-time internet access supplied by satellites
  • Detecting and reporting leaks

The report says a new generation of technology, including AI and real-time analytics, is transforming office and on-site operations at oil and gas companies. The Trump administration’s “focus on AI innovation through supportive policies and investments could further accelerate large-scale adoption and digital transformation,” the report adds.

Chevron and ExxonMobil, the two biggest oil and gas companies based in the Houston area, continue to dive deeper into AI.

Chevron is taking advantage of AI to squeeze more insights from enormous datasets, VentureBeat reported.

“AI is a perfect match for the established, large-scale enterprise with huge datasets—that is exactly the tool we need,” Bill Braun, the company’s now-retired chief information officer, said at a VentureBeat event in May.

Meanwhile, AI enables ExxonMobil to conduct autonomous drilling in the waters off the coast of Guyana. ExxonMobil says its proprietary system improves drilling safety, boosts efficiency, and eliminates repetitive tasks performed by rig workers.

ExxonMobil is also relying on AI to help cut $15 billion in operating costs by 2027.

“There is a concerted effort to make sure that we’re really working hard to apply that new technology … to drive effectiveness and efficiency,” Darren Woods, executive chairman and CEO of ExxonMobil, said during a 2024 earnings call.

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