Despite its high energy production, Texas has had more outages than any other state over the past five years due to the increasing frequency and severity of extreme weather events and rapidly growing demand. Photo via Getty Images

Texas stands out among other states when it comes to energy production.

Even after mass rolling blackouts during Winter Storm Uri in 2021, the Lone Star State produced more electricity than any other state in 2022. However, it also exemplifies how challenging it can be to ensure grid reliability. The following summer, the state’s grid manager, the Electrical Reliability Council of Texas (ERCOT), experienced ten occasions of record-breaking demand.

Despite its high energy production, Texas has had more outages than any other state over the past five years due to the increasing frequency and severity of extreme weather events and rapidly growing demand, as the outages caused by Hurricane Beryl demonstrated.

A bigger storm is brewing

Electric demand is poised to increase exponentially over the next few years. Grid planners nationwide are doubling their five-year load forecast. Texas predicts it will need to provide nearly double the amount of power within six years. These projections anticipate increasing demand from buildings, transportation, manufacturing, data centers, AI and electrification, underscoring the daunting challenges utilities face in maintaining grid reliability and managing rising demand.

However, Texas can accelerate its journey to becoming a grid reliability success story by taking two impactful steps. First, it could do more to encourage the adoption of distributed energy resources (DERs) like residential solar and battery storage to better balance the prodigious amounts of remote grid-scale renewables that have been deployed over the past decade. More DERs mean more local energy resources that can support the grid, especially local distribution circuits that are prone to storm-related outages. Second, by combining DERs with modern demand-side management programs and technology, utilities can access and leverage these additional resources to help them manage peak demand in real time and avoid blackout scenarios.

Near-term strategies and long-term priorities

Increasing electrical capacity with utility-scale renewable energy and storage projects and making necessary electrical infrastructure updates are critical to meet projected demand. However, these projects are complex, resource-intensive and take years to complete. The need for robust demand-side management is more urgent than ever.

Texas needs rapidly deployable solutions now. That’s where demand-side management comes in. This strategy enables grid operators to keep the lights on by lowering peak demand rather than burning more fossil fuels to meet it or, worse, shutting everything off.

Demand response, a demand-side management program, is vital in balancing the grid by lowering electricity demand through load control devices to ensure grid stability. Programs typically involve residential energy consumers volunteering to let the grid operator reduce their energy consumption at a planned time or when the grid is under peak load, typically in exchange for a credit on their energy bill. ERCOT, for example, implements demand responseand rate structure programs to reduce strain on the grid and plans to increase these strategies in the future, especially during the months when extreme weather events are more likely and demand is highest.

The primary solution for meeting peak demand and preventing blackouts is for the utility to turn on expensive, highly polluting, gas-powered “peaker” plants. Unfortunately, there’s a push to add more of these plants to the grid in anticipation of increasing demand. Instead of desperately burning fossil fuels, we should get more out of our existing infrastructure through demand-side management.

Optimizing existing infrastructure

The effectiveness of demand response programs depends in part on energy customers' participation. Despite the financial incentive, customers may be reluctant to participate because they don’t want to relinquish control over their AC. Grid operators also need timely energy usage data from responsive load control technology to plan and react to demand fluctuations. Traditional load control switches don’t provide these benefits.

However, intelligent residential load management technology like smart panels can modernize demand response programs and maximize their effectiveness with real-time data and unprecedented responsiveness. They can encourage customer participation with a less intrusive approach – unlocking the ability for the customer to choose from multiple appliances to enroll. They can also provide notifications for upcoming demand response events, allowing the customer to plan for the event or even opt-out by appliance. In addition to their demand response benefits, smart panels empower homeowners to optimize their home energy and unlock extended runtime for home batteries during a blackout.

Utilities and government should also encourage the adoption of distributed energy resources like rooftop solar and home batteries. These resources can be combined with residential load management technology to drastically increase the effectiveness of demand response programs, granting utilities more grid-stabilizing resources to prevent blackouts.

Solar and storage play a key role

During the ten demand records in the summer of 2023, batteries discharging in the evening helped avoid blackouts, while solar and wind generation covered more than a third of ERCOT's daytime load demand, preventing power price spikes.

Rooftop solar panels generate electricity that can be stored in battery backup systems, providing reliable energy during outages or peak demand. Smart panels extend the runtime of these batteries through automated energy optimization, ensuring critical loads are prioritized and managed efficiently.

Load management technology, like smart panels, enhances the effectiveness of DERs. In rolling blackouts, homeowners with battery storage can rely on smart panels to manage energy use, keeping essential appliances operational and extending stored energy usability. Smart panels allow utilities to effectively manage peak demand, enabling load flexibility and preventing grid overburdening. These technologies and an effective demand response strategy can help Texans optimize the existing energy capacity and infrastructure.

A more resilient energy future

Texas can turn its energy challenges into opportunities by embracing advanced energy management technologies and robust demand-side strategies. Smart panels and distributed energy resources like solar and battery storage offer a promising path to a resilient and efficient grid. As Texans navigate increasing electricity demands and extreme weather events, these innovations provide hope for a future where reliable energy is accessible to all, ensuring grid stability and enhancing the quality of life across the state.

------

Kelly Warner is the CEO of Lumin, a responsive energy management solutions company.

This article originally ran on EnergyCapital.
Ad Placement 300x100
Ad Placement 300x600

CultureMap Emails are Awesome

Houston college joins inaugural workforce accelerator supported by Google

hands-on training

Houston City College (HCC) is one of 15 community colleges from around the country to be selected for the first-ever Workforce Futures Accelerator.

The three-year effort is supported by Google.org, the tech company’s philanthropic arm, and led by the Association of Community College Trustees (ACCT), a non-profit educational organization that represents over 500 community, junior, and technical colleges. The accelerator focuses on helping colleges embed virtual, employer-sponsored training opportunities into short-term workforce training programs, giving participants access to opportunities that they might otherwise receive through internships or other "work-based learning" stints.

"The Workforce Futures Accelerator reflects the Houston City College mission of offering a high-quality, affordable education for workforce training and career development," Pretta VanDible Stallworth, HCC trustee and chair-elect of the ACCT board of directors, said in a news release. "Advancing student success and creating pathways to opportunities ensures that our students are well equipped to succeed and build a secure future in today's economy.”

Through the accelerator, HCC is tasked with fusing online project-based learning opportunities with its workforce education programs. The idea is to give students hands-on experiences working on projects sponsored by employers, allowing them to gain real-world knowledge in the process.

HCC will select two workforce programs that meet the accelerator’s criteria and insert into them into coursework. In the second and third year of the accelerator, the selected colleges are expected to scale the programs by adding instructors and programs to develop a network of to support their continued implementation.

“Participation by HCC will strengthen how we provide students with career-connected learning experiences that complement their classroom education and align with the needs of employers,” HCC Chancellor Margaret Ford Fisher added in the news release. “We are focused on ‘future forward’ strategies to meet the present and future needs of our region’s businesses.”

Two other Texas colleges were chosen to participate in the accelerator: Lamar Institute of Technology in Beaumont and Grayson College in Denison.

The remaining cohort includes:

  • Bergen Community College in Paramus, New Jersey
  • Central Louisiana Community College in Alexandria, Louisiana
  • Clark State College in Springfield, Ohio
  • Great Basin College in Elko, Nevada
  • Heartland Community College in Normal, Illinois
  • Hudson County Community College in Jersey City, New Jersey
  • Manchester Community College in Manchester, New Hampshire
  • Mesa Community College in Mesa, Arizona
  • Mohave College in Kingman, Arizona
  • San Joaquin Delta Community College in Stockton, California
  • San Juan College in Farmington, New Mexico
  • West Virginia University Parkersburg in Parkersburg, West Virginia

New report ranks Texas among top 10 states where AI could disrupt jobs

AI Workforce

A new nationwide report examining where AI could "reshape" the most jobs has ranked Texas No. 9 among the most at-risk states for AI job disruption.

The new SmartAsset report compared all 50 states and the District of Columbia to calculate the estimated percent of the workforce employed in the 26 occupations with the highest AI exposure, as determined by June 2026 research by the Virginia Economic Information and Analytics Division.

The findings revealed that 500,000 Texas workers, or 3.55 percent of the total workforce, are employed in occupations with "high exposure to potential AI disruption."

This also places the Lone Star State as the 9th most at-risk state in the U.S. where AI exposure can lead to "declining hiring demand, wage pressure, task automation, and other forms of disruption."

"States with larger concentrations of highly exposed occupations could experience more pronounced labor-market changes, particularly in roles where core tasks are more vulnerable to AI-driven restructuring," the report's author wrote.

Texas' biggest cities, like Houston and Austin, are known for their thriving tech and business industries, and the study noted that many of the occupations within those sectors are the most at risk. The Virginia Economic Information and Analytics Division said the top five most AI-exposed occupations in the U.S. are: mathematicians, proofreaders, correspondence clerks, court reporters, and media and communication workers. Additionally, computer programmers, database administrators, web developers, telephone operators, and communications equipment operators round out the top 10 most at-risk positions.

These are the 16 remaining occupations most exposed to AI disruption, in order:

  • Data Entry Keyers
  • Statistical Assistants
  • Office Support Workers
  • Interpreters and Translators
  • Database Architects
  • Software Quality Assurance Analysts
  • Medical Transcriptionists
  • Software Developers
  • Writers and Authors
  • Payroll Clerks
  • Web Designers
  • Miscellaneous Computer Occupations
  • Insurance Claims Processors
  • Telemarketers
  • Computer Numerically Controlled Tool Programmers
  • Bookkeeping and Accounting Clerks

A separate SmartAsset report from April 2026 found about 20.5 percent of Texas workers use AI to do their jobs in some capacity. That trend will continue to shift further as employers and employees choose to adopt — or reject — AI implementation.

Across the U.S., Washington topped the list as the state with the highest concentration of AI-exposed jobs, with nearly 5.7 percent of the state's workforce employed in the 26 most at-risk positions. SmartAsset said Washington's high prevalence of technology companies is a significant factor that skyrocketed the state to the top of the list.

"Home to major technology companies including Microsoft, Amazon, T-Mobile and Expedia, the state has large numbers of computer programmers and software developers, two occupations with high exposure," the report said.

Meanwhile, Mississippi ranked No. 51 with the lowest concentration of AI-exposed jobs in the nation. About 22,500 workers in Mississippi, or 1.93 percent of its workforce, are at risk for AI disruption.

The top 10 states where AI could reshape the most jobs are:

  • No. 1 – Washington
  • No. 2 – Virginia
  • No. 3 – District of Columbia
  • No. 4 – California
  • No. 5 – Utah
  • No. 6 – Maryland
  • No. 7 – Colorado
  • No. 8 – New Hampshire
  • No. 9 – Texas
  • No. 10 – North Carolina
---

This article originally appeared on CultureMap.com.

UH lands $1.2M NIH grant to fight superbugs using AI, quantum sensing

drug defense

The fight against antibiotic-resistant bacteria like MRSA is getting science fiction-like upgrades at the University of Houston thanks to a new four-year, $1.26 million grant from the National Institutes of Health.

The university says the recent funding brings total federal support up to $3.5 million for 11 years for the project, which uses AI and quantum-sensing technology to better understand how bacterial proteins develop resistance to drugs.

Any medical professional will tell you that one of the worst things that can happen is almost killing an infection. Bacteria that survive attacks from conventional antibiotic treatments emerge tougher, more resistant and more aggressive than before–making them much harder to treat. A good example is the superbug methicillin-resistant Staphylococcus aureus (MRSA).

UH chemistry professors Yuhong Wang and Shoujun Xu are working on this issue. They know full well that fighting superbugs requires new technology and new approaches, which is what they aim to pioneer with their new grant.

“Drug-resistant bacterial infections such as MRSA are becoming harder to treat, creating an urgent need for faster ways to understand how antibiotics and other small molecules interact with bacterial proteins,” Wang said in a news release.

Wang and Xu’s work centers around GTP, a cellular fuel that can cause tiny changes to a cell's structure when it mutates. Sometimes, those shape changes make it easier for drugs to breach the wall and attack the cells.

The UH scientists are employing AlphaFold, an AI-powered tool that can scan large molecular libraries in seconds. From these models, they can see promising drug combinations for future testing.

Once identified, the team uses their invention, super-resolution force spectroscopy, to monitor the cells. Tiny magnetic beads are attached to genetic material, then magnified to see how strong that material is when pulled. They can measure this incredible microscopic process through an atomic magnetometer, typically used in quantum physics. Combined, all these tools allow a high-definition look at how each molecule might respond to new chemical approaches.

“We're the only chemists in the world that use an atomic magnetometer for biological research,” Xu said. “It's a technique developed by physicists, and there is usually a gap between techniques developed by physicists and biological applications. Yuhong and I have been bridging that gap together for the past 10 years.”

Eventually, Wang and Xu hope to develop powerful software that can be used by drug manufacturers to model cellular responses. With enough predictive data, the software could even get ahead of superbugs’ own mutation, allowing drugs to be developed before new strains arrive.

"We want an algorithm where you input a protein sequence, score the mutation hotspots, and develop new inhibitors before a drug-resistant species even emerges," Wang added.