Houston energy expert asks: Who pays when AI outruns the power grid?

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Scotty Nyquist discuss the growth in AI data centers and the strain on the system. Photo via HARC report

For most of the past 20 years, U.S. electricity policy relied on predictable trends in demand. Electricity use, in most regions, increased gradually, forecasts were stable, and utilities adjusted the system in small steps. Power plants, transmission lines, and substations were generally added to reflect shifts in load, rather than growth, and costs were recovered through modest adjustments to customer bills.

Growth in AI data centers has disrupted this model. A single facility can add as much electricity demand as a small town. That demand comes all at once, runs continuously, and has little tolerance for outages. If electricity service drops even briefly, computation stops, and services shut down. Ironically, data centers need reliable service, a point that their emergence is driving concern around for the rest of the grid.

What the numbers say

The International Energy Agency projects global electricity consumption from data centers to double by 2030, reaching roughly 945 TWh, nearly 3 percent of global electricity demand, with consumption growing about 15 percent per year this decade. McKinsey projects that U.S. data center demand alone could grow 20–25 percent per year, with global capacity demand more than tripling by 2030.

After years of roughly 0.5 percent annual demand growth, many forecasts now place total U.S. electricity demand growth closer to 2–3 percent per year through the mid-2030s, with much higher growth in specific regions. In Texas, some forecasters are saying electricity demand could double over the next five years, a staggering 10 percent per year growth rate. What sounds incremental on paper translates into a major challenge on the ground. Meeting this pace of growth is estimated to require $250–$300 billion per year in grid investment, about double what the system has been absorbing.

Where the system starts to strain

The strain appears first in the interconnection queue. It shows up as long waits, backlogs, and delays for connecting new loads and new generation.

Before new generators or large load customers can be connected, a study is required to assess their impact on the grid, whether it can physically handle the added load, and whether upgrades are required. With AI-driven data centers, utilities face far more connection requests than they can realistically support. In ERCOT, large-load interconnection requests exceed 200 gigawatts, most tied to data centers. That amount exceeds historical norms, and it is several times larger than what can be practically studied or built in the near term.

To be clear, public utility commissions are required to study these requests because they must manage system capabilities to ensure minimal disruption. This means engineers spend time evaluating projects that may never be built, while other more commercially viable projects may wait longer for approvals. This extends timelines and makes infrastructure planning less reliable.

Why policymakers are rethinking the rules

Utilities and their regulators must decide how much generation, transmission, and substation capacity to build years before it comes online. Those decisions are based on expected demand at the time projects are approved. When it comes to data centers, by the time infrastructure is completed, they may end up deploying newer, more efficient chips that use less power than originally assumed. This can result in grid infrastructure built for a higher load than what actually materializes, leaving excess capacity that still must be paid for through system-wide rates.

That’s the central dilemma. If utilities build too little capacity, the system operates with less reserve margin. During periods of grid stress, operators have fewer options, increasing the likelihood of curtailments or outages. However, if utilities build too much, customers may be asked to pay for infrastructure that is not fully used.

In response, policymakers are adjusting the rules. In some regions, regulators are moving toward bring-your-own-power approaches that require large data centers to supply or fund part of the capacity needed to serve them or reduce demand during system stress. At the federal level, permitting reforms tied to datacenter infrastructure increasingly treat electricity as a strategic economic input.

As Ken Medlock, senior director at the Baker Institute Center for Energy Studies (CES), explains:

“Many of the planned data centers are now also adding behind-the-meter options to their development plans because they do not anticipate being able to manage their needs solely from the grid, and they certainly cannot do so with only intermittent power sources.”

Behind-the-meter (BTM) refers to power that a consumer controls on its side of the utility meter, such as on-site gas generation or a dedicated power plant. These resources allow data centers to keep operating during grid-related service. Most facilities remain connected to the grid, but the backup BTM generation serves as insurance for operating their core business.

This shifts responsibility. Utilities traditionally manage reliability across all customers by maintaining an operating reserve margin, or spare capacity. Increasingly, large-load customers manage part of their own electricity reliability needs, which changes how infrastructure is planned and how risk is distributed.

Bottom line

AI-driven load growth is arriving faster and in more concentrated places than the power system was built to accommodate. Utilities and regulators are being forced to make decisions sooner than planned about where to build, how fast to build, and which customers get priority when capacity is limited. The effects extend beyond data centers, showing up in system costs, reliability margins, competition for grid access, and pressure on communities and industries that depend on affordable and dependable power. The issue is not whether electricity can be generated, but how the costs and risks of rapid demand growth are distributed as the system tries to keep up. How regulators balance these decisions will determine who pays as AI demand outruns the power grid.

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Scott Nyquist is a senior advisor at McKinsey & Company and vice chairman, Houston Energy Transition Initiative of the Greater Houston Partnership. The views expressed herein are Nyquist's own and not those of McKinsey & Company or of the Greater Houston Partnership. This article originally appeared on LinkedIn.

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Collide has rolled out RIGGS, a large language model for energy professionals. Photo via Getty Images

Houston AI startup rolls out platform to reshape oil and gas workflows

AI for energy

Houston-based Collide is looking to solve AI issues in the energy industry from within.

Co-founded by former oil roughneck Collin McLelland, the company has developed AI software for operators and field teams, shaped by firsthand oilfield experience. Its AI-native platform “retrieves and synthesizes data from authoritative sources to deliver accurate, cited, and energy-focused insights to oil and gas professionals,” according to the company.

“Oil and gas has a graveyard full of technology that was technically impressive and operationally useless,” McLelland tells Energy Capital. “The reason is almost always the same: the people who built it didn't understand what they were actually solving for. When you're an outsider, you see workflows and try to automate them. When you're an insider, you understand why those workflows exist—the regulatory constraints, the physical realities, the liability concerns, the trust dynamics between operators and service companies.”

Collide’s large language model, known as RIGGS, performed well in recent benchmarking results when taking a standardized petroleum engineering (SPE) exam, the company reports. The exam assesses understanding from conceptual terminology to complex mathematical problem-solving.

According to Collide, RIGGS achieved a score of 67.5 percent on a 40-question subset of the SPE petroleum engineering exam, outperforming other large language models like Grok 4 (62.5 percent), Claude Sonnet 4.5 (52.5 percent) and GPT 5.1 (4 percent).

RIGGS completed the test in 15 minutes, while Grok took two hours. Collide hopes over the next few months, RIGGS will receive a score between 75 percent to 80 percent accuracy.

The software could potentially help oil and gas companies produce accurate outputs and automate trivial workflows, which can open up valuable time for engineers and teams to work on other pressing matters, according to McLelland.

“Collide exists because we sat in those seats — we were the engineers, the operators, the field guys,” he says. ”RIGGS scoring higher on the PE exam versus the frontier labs isn't a party trick. It's evidence that the model understands petroleum engineering the way a petroleum engineer does, because it was built by people who do.”

RIGGS was trained on Collide’s Spindletop hardware and is supported by a vast library of information, as well as a reasoning engine and validation layer that uses logic to solve problems.

“Longer term, we see RIGGS as the intelligence layer that sits underneath every operator's workflow — not a chatbot you open in a browser, but something embedded in the tools engineers already use,” McLelland says. “The goal is to give every engineer the knowledge and pattern recognition of a 30-year veteran, on demand."

According to McLelland, Collide is already building toward reservoir analysis and production optimization, automated regulatory compliance (Railroad Commission filings, W-10s, G-10s), workover report generation, and engineering decision support in the field for near-term use cases. In March, Collide and Texas-based oil and gas operator Winn Resources announced a collaboration to automate the time-intensive process of filing monthly W-10 and G-10 forms with the Texas Railroad Commission, completing what’s normally a multi-hour task in under 30 minutes. Collide reports that Winn’s infrastructure now automates regulatory filings and provides real-time visibility into data gaps, which has reduced processing time by over 95 percent.

“Before Collide, I'd spend hours manually keying in filings,” Buck Crum, director of operations, said in a news release. “(In March), we had 50 wells to file and I was done in 20 minutes. It does the majority of the heavy lifting while keeping me in control. That human-in-the-loop approach saves meaningful time and gives us greater confidence in our compliance and reporting.”

Collide was originally launched by Houston media organization Digital Wildcatters as “a professional network and digital community for technical discussions and knowledge sharing.” After raising $5 million in seed funding led by Houston’s Mercury Fund last year, the company said it would shift its focus to rolling out its enterprise-level, AI-enabled solution.

Hadi Ghasemi, a University of Houston professor, has uncovered a method to release heat from data centers and electronics at record performance. Photo courtesy UH.

Houston researcher develops efficient method to cool AI data centers

cool findings

A University of Houston professor has developed a new cooling method that can remove heat at least three times more effectively from AI data centers than current technologies.

Hadi Ghasemi, a distinguished professor of Mechanical & Aerospace Engineering at UH, published his findings in two articles in the International Journal of Heat and Mass Transfer. The findings solve a critical issue in the growing AI sector, according to UH.

High-powered AI data centers generate huge amounts of heat due to the GPU and operating systems they use with extreme power densities, which introduce complex thermal challenges. Traditionally, cooling methods, like microchannels, which use flow and spray cooling, have had limitations when exposed to extreme heat flux, according to UH.

Ghasemi’s research, however, found a more effective way to design thin-film evaporation structures to release heat from data centers and electronics at record performance.

Ghasem’s solution coupled topology optimization and AI modeling to determine the best shapes for thin film efficiency, ultimately landing on a branch-like structure—resembling a tree.

The model found that the “branches” needed to be about 50 percent solid and 50 percent empty space for optimum efficiency, and that they could sustain high heat fluxes with minimal thermal resistance.

“These structures could achieve high critical heat flux at much lower superheat compared to traditionally studied structures,” Ghasemi said in a news release. “The new structures can remove heat without having to get as hot as previous removal systems.

Ghasemi’s doctoral candidates, Amirmohammad Jahanbakhsh and Saber Badkoobeh Hezave, also worked on the project. The team believes their results show the impact of a physics-aware, AI design and can help ensure reliability, longevity and stability of AI data centers.

“Beyond achieving record performance, these new findings provide fundamental insight into the governing heat-transfer physics and establishes a rational pathway toward even higher thermal dissipation capacities,” Ghasemi added in the release

Merab Momen, founder of AI CTO Services. Courtesy Photo

How this Houston expert helps startups turn AI hype into real impact

now streaming

Artificial intelligence is now everywhere. It is mentioned in every startup pitch deck, and every corporate roadmap claims to use it. However, many early-stage businesses struggle with the simple question, “What does AI actually mean for my business?”

In a recent podcast episode of EnergyTech Startups, Merab Momen, founder of AI CTO Services and a long time AI practitioner, explains why most founders misunderstand AI, how startups can practically apply it and why Houston is quietly becoming a serious hub for AI-driven innovation.

Filling the AI Leadership Gap

Merab’s career has spanned decades of technology transitions. He worked on neutral networks in the 1990s, constructed computer vision systems long before they were common, and helped install AI solutions inside huge industrial companies. However, he noticed a huge problem when generative AI started to explode into the mainstream-The requirement of a real partner by the founders for AI integration but inability to rely on a full-time CTO and project-based consultants.

“I really needed something which is much more engaging where I can give that partner-level advice to the founders,” he said. By giving firms on-demand access to high-level AI knowledge and expertise, his methodology enables them to analyse tools, steer clear of cost blunders and eventually transition to a permanent technology leader when the time is right.

AI is Older than Most People Think

Despite its recent rise in popularity, AI is nothing new. AI actually began in the 1950s. Merab in his conversation explained how he worked on his first AI project back in the year 1996 that worked perfectly, but the processing power wasn’t just there to make it practical. He continued how he utilized the swarm intelligence models to optimize supply chains, now referred to as MLPOs and data engineering.

From Language Models to Physical World

Much of the public conversation about AI revolves around chatbots and text generation. But Merab sees far greater potential in AI’s interaction with the physical world, especially in industrial settings. He emphasized edge computing and vision language models (VLMs) as significant advances in manufacturing and energy. This physical shift is opening doors for new opportunities for robotics, automated inspections, and industrial safety applications. Merab added that Houston is uniquely positioned for this transition.

Why Houston has an AI Advantage

Silicon Valley may dominate the AI headlines, but Merab believes Houston’s advantage lies beneath the surface. The city doesn’t lag in AI utilization; it just operates in industries where results show differently.

Machine learning isn’t new to Houston’s core industries. Energy companies, manufacturers, logistics providers, and healthcare systems have been using advanced analytics for decades. The difference lies in them innovating in industrial sectors rather than consumer technology.

What’s Next

With the AI CTO Services growing, Merab is working with startups across industries to deploy AI in practical, business-first ways.

He is more interested in assisting founders in finding answers to critical issues than following new trends.

For Houston’s energy and climate tech community, it needs to transform AI enthusiasm into real-world impact.

Listen to the full conversation with Mehrab Momin on the Energy Tech Startups Podcast to learn more.

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Energy Tech Startups Podcast is hosted by Jason Ethier and Nada Ahmed. It delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.

A new report shows the role Texas could play as the data-center sector enters "hyperdrive." Photo via JLL.com.

Texas could topple Virginia as biggest data-center market by 2030, JLL report says

data analysis

Everything’s bigger in Texas, they say—and that phrase now applies to the state’s growing data-center presence.

A new report from commercial real estate services provider JLL says Texas could overtake Northern Virginia as the world’s largest data-center market by 2030. Northern Virginia is a longtime holder of that title.

What’s driving Texas’ increasingly larger role in the data-center market? The key factor is artificial intelligence.

Companies like Google and Microsoft need more energy-hungry data centers to power AI innovations. In a 2023 article, Forbes explained that AI models consume a lot of energy because of the massive amount of data used to train them, as well as the complexity of those models and the rising volume of tasks assigned to AI.

“The data-center sector has officially entered hyperdrive,” Andy Cvengros, executive managing director at JLL and co-leader of its U.S. data-center business, said in the report. “Record-low vacancy sustained over two consecutive years provides compelling evidence against bubble concerns, especially when nearly all our massive construction pipeline is already pre-committed by investment-grade tenants.”

Dallas-Fort Worth has long dominated the Texas data-center market. But in recent years, West Texas has emerged as a popular territory for building data-center campuses, thanks in large part to an abundance of land and energy. Nearly two-thirds of data-center construction underway now is happening in “frontier markets” like West Texas, Ohio, Tennessee and Wisconsin, the JLL report says.

Northern Virginia, the current data-center champ in the U.S., boasted a data-center market with 6,315 megawatts of capacity at the end of 2025, the report says. That compares with 2,423 megawatts in Dallas-Fort Worth, 1,700 megawatts in the Austin-San Antonio corridor, 200 megawatts in West Texas, and 164 megawatts in Houston.

Google is investing in Texas. Courtesy of Google

Google's $40B investment in Texas data centers includes energy infrastructure

The future of data

Google is investing a huge chunk of money in Texas: According to a release, the company will invest $40 billion on cloud and artificial intelligence (AI) infrastructure, with the development of new data centers in Armstrong and Haskell counties.

The company announced its intentions at a meeting on November 14 attended by federal, state, and local leaders including Gov. Greg Abbott who called it "a Texas-sized investment."

Google will open two new data center campuses in Haskell County and a data center campus in Armstrong County.

Additionally, the first building at the company’s Red Oak campus in Ellis County is now operational. Google is continuing to invest in its existing Midlothian campus and Dallas cloud region, which are part of the company’s global network of 42 cloud regions that deliver high-performance, low-latency services that businesses and organizations use to build and scale their own AI-powered solutions.

Energy demands

Google is committed to responsibly growing its infrastructure by bringing new energy resources onto the grid, paying for costs associated with its operations, and supporting community energy efficiency initiatives.

One of the new Haskell data centers will be co-located with — or built directly alongside — a new solar and battery energy storage plant, creating the first industrial park to be developed through Google’s partnership with Intersect and TPG Rise Climate announced last year.

Google has contracted to add more than 6,200 megawatts (MW) of net new energy generation and capacity to the Texas electricity grid through power purchase agreements (PPAs) with energy developers such as AES Corporation, Enel North America, Intersect, Clearway, ENGIE, SB Energy, Ørsted, and X-Elio.

Water demands

Google’s three new facilities in Armstrong and Haskell counties will use air-cooling technology, limiting water use to site operations like kitchens. The company is also contributing $2.6 million to help Texas Water Trade create and enhance up to 1,000 acres of wetlands along the Trinity-San Jacinto Estuary. Google is also sponsoring a regenerative agriculture program with Indigo Ag in the Dallas-Fort Worth area and an irrigation efficiency project with N-Drip in the Texas High Plains.

In addition to the data centers, Google is committing $7 million in grants to support AI-related initiatives in healthcare, energy, and education across the state. This includes helping CareMessage enhance rural healthcare access; enabling the University of Texas at Austin and Texas Tech University to address energy challenges that will arise with AI, and expanding AI training for Texas educators and students through support to Houston City College.

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This article originally appeared on CultureMap.com.

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Texas awards $73M for Houston-area grid resilience project

grid funding

Texas Gov. Gregg Abbott announced millions in funding for energy resilience projects around this state this week, with one major project set to impact the greater Houston area.

As part of the Texas Energy Fund's Outside of ERCOT Grant Program, the state announced a roughly $73 million agreement with the Sam Houston Electric Cooperative to replace and upgrade more than 9,000 electric poles and improve other equipment in Montgomery, Liberty and Hardin counties. The agreement is the first for the fund's Outside of ERCOT Grant Program, which supports state projects outside of the state's largest grid.

The multibillion-dollar Texas Energy Fund aims to "finance the construction, maintenance, and modernization of electric facilities across Texas." It was approved by voters in 2023. Other programs within the fund include the:

In-ERCOT Generation Loan Program
Completion Bonus Grant Program
Texas Backup Power Package Program

“The Texas Energy Fund delivers real results for Texans and strengthens the electric systems that families, businesses, and communities depend on,” Abbott said in a news release. “This grant to Sam Houston Electric Cooperative will replace thousands of vulnerable utility poles to better withstand severe weather and ensure a more reliable and resilient grid in East Texas.”

The Houston-area project, nicknamed Steel Anchor, is expected to be completed by June 2031. According to the release from the governor's office, the Sam Houston Electric Cooperative’s territory is one of the most hurricane-prone service areas in the state. The cooperative serves more than 38,000 Texas consumers

“Over the past decade, Sam Houston EC has strategically replaced poles to improve the strength of its electricity distribution system. This grant will boost the Cooperative’s ongoing grid-hardening and resiliency program,” Doug Turk, CEO of the Sam Houston Electric Cooperative, added in the release.

Following the announcement of the Sam Houston funding, Abbott's office also awarded another $200 million from the Outside of ERCOT Grant Program to upgrade approximately 700 miles of power equipment in Northeast Texas. The equipment is operated by Southwestern Electric Power Company, which serves more than 192,000 Texas consumers. The project will include improvements to 200 circuits, replacing aging copper wire with aluminum alloy conductors and replacing existing utility poles.

Additionally, the state announced its seventh Texas Energy Fund loan agreement for a 570 megawatt natural gas power plant in Sherman, Texas. The 20-year loan of up to $411 million is between the Public Utility Commission of Texas and Rayburn Electric Cooperative and is part of the fund's In-ERCOT Generation Loan Program. Rayburn will build the facility near its existing Rayburn Energy Station 1 in the Texoma region. It will connect to the ERCOT North Load Zone.

“When Texas voters overwhelmingly approved the Texas Energy Fund, they gave us a mandate to secure new, reliable power generation for Texas,” PUCT Chairman Thomas Gleeson added in a release. “The TxEF is delivering on that promise, and Rayburn Electric Cooperative’s new 570 MW power plant is proof. We are ensuring Texas families and businesses have power they can depend on for years to come.”

Solar manufacturer announces massive new facility in Houston area

coming soon

SEG Solar has announced plans to open a new 1.15 million-square-foot solar module facility in Tomball—its third in the Houston area.

The news comes just weeks after the Houston-based solar manufacturer announced its second facility, which will be located in Cypress. It’s expected to open in August.

The latest 4.6-gigawatt facility in Tomball will include an assembly factory and a warehouse. Construction is slated to wrap in March 2027, with commercial panel production planned to begin in May 2027. Once completed, the facility will bring SEG’s annual U.S. module manufacturing capacity to 10.6 gigawatts, according to a news release from the company, one of the largest totals in the country.

The facility will produce heterojunction technology (HJT) modules, which the company says will add to the number of n-type solar panels made in the U.S. HJT modules are known to be more durable and are well suited for hotter climates.

“Designed to support next-generation HJT technology and FEOC-compliant production, the facility ensures reliable, high-efficiency solar solutions,” Raymond Bailey, sales manager at SEG Solar, said in a LinkedIn post. “ Alongside upstream integration in Indonesia and potential U.S. cell manufacturing, we are strengthening supply chain resilience amid evolving trade policies.”

SEG opened its $60 million, 250,000-square-foot facility in Houston in 2024 to house its production workshops, raw material warehouses, administrative offices, finished goods warehouses, and supporting infrastructure. The continued expansion is part of SEG’s long-term goal of becoming one of the largest 100 percent U.S.-owned module manufacturers.

Houston chemical co. completes successful field trial of cleaner natural gas processing tech

successful trial

Houston-based Merichem Technologies has announced successful results from the field trial of its new hydrogen sulfide (H2S) removal technology in the Permian Basin.

The technology, known as ECOTREAT, removed more than 99 percent of hydrogen sulfide gas from natural gas streams, or “sour gas,” without producing solid waste during the month-long trial. It also showed sustained performance even when operating above the unit’s design capacity, according to a news release.

“The industry is continually seeking to reduce both the price and complexity of removing hydrogen sulfide from gas production, especially since oil production has shifted to increasingly sour sources, higher gas ratios, and higher water ratios,” Jeff Gomach, SVP, Merichem Technologies, said in a news release. “ECOTREAT met all its field trial objectives and provides a highly effective method for removing hydrogen sulfide to prevent equipment corrosion, ensure worker safety, meet environmental regulations, and maintain product quality for transport.

H2S found in natural gas can turn the gas toxic or hazardous and lead to corrosion in pipelines and processing equipment. However, standard H2S removal technologies create high levels of solid waste. ECOTREAT resolves many of those issues by using an aqueous-phase proprietary catalytic process that converts H2S into dissolved thiosulfate.

Next, Merichem says it plans to move the technology out of the pilot stage to full-scale commercialization.

Merichem, an 80-plus-year-old company, initially launched as a soap and industrial cleaning company. It eventually transitioned to focus on energy technology.

In 2024, Black Bay Energy acquired a portion of Merichem Process Technologies and Merichem Catalyst Products, which would become Merichem Technologies.

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