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Wall Street backs Rick Perry’s $19 billion nuclear-powered data center venture, Fermi America, combining nuclear energy, AI infrastructure, and data centers to meet soaring electricity demand and attract major investors betting on America’s clean energy technology future.

What is "Wall Street Backs Rick Perry’s $19 Billion Nuclear-Powered Data Center Venture”?

Wall Street is backing Rick Perry’s $19 billion nuclear-powered data center venture because it combines the explosive growth of AI with the promise of clean, reliable nuclear energy.

✅ Addresses AI’s massive power demands with nuclear generation

✅ Positions Fermi America as a pioneer in energy-tech convergence

✅ Reflects investor confidence in long-term clean energy solutions

Former Texas Governor and U.S. Energy Secretary Rick Perry has returned to the energy spotlight, this time leading a bold experiment at the intersection of nuclear power and artificial intelligence. His startup, Fermi America, headquartered in Amarillo, Texas, went public this week with an initial valuation of $19 billion after its shares surged 55 percent above the opening price on the first day of trading.

The company aims to tackle one of the most pressing challenges in modern technology: the staggering energy demand of AI data centers. “Artificial intelligence, which is getting more and more embedded in all parts of our lives, the servers that host the data for artificial intelligence are stored in these massive warehouses called data centers,” said Houston Chronicle energy reporter Claire Hao. “And data centers use a ton of electricity.”

Fermi America’s plan, Hao explained, is as ambitious as it is unconventional. Fermi America has a proposal to build what it claims will be the world’s largest data center, powered by what it asserts will be the country’s largest nuclear complex. So very ambitious plans.”

According to the company’s roadmap, Fermi aims to bring its first mega reactor online by 2032, followed by three additional large reactors. In the meantime, the firm intends to integrate natural gas and solar energy by the end of next year to support early-stage operations.

While much of the energy sector’s attention has turned toward small modular reactors, Fermi’s approach focuses on traditional large-scale nuclear technology. “What Fermi is talking about building are large traditional reactors,” Hao said. “These very large traditional reactors are a tried and true technology. But the nuclear industry has a history of taking a very long time to build them, and they are also very expensive to build.” She noted that the most recent example, completed in 2023 by a Georgia utility, came in $17 billion over budget and several years late.

To mitigate such risks, Fermi has recruited specialists with international experience. “They’ve hired folks that have successfully built these projects in China and in other countries where it has been a lot smoother to build these,” Hao said. “Fermi wants to try to make it a quicker process.”

Perry’s involvement lends both visibility and controversy. In addition to co-founding the company, Griffin Perry, his son, plays a role in its management. The firm has hinted that it might even name reactors after former President Donald Trump, under whom Perry served as Secretary of Energy. Perry has framed the project as part of a national effort to regain technological ground. “He really wants to help the U.S. catch up to countries like China when it comes to delivering nuclear power for the AI race,” Hao explained. “He says we’re already behind.”

Despite the fanfare, Fermi America is still a fledgling enterprise. Founded in January and announced publicly in June, the company reported a $6.4 million loss in the first half of the year and has yet to generate any revenue. Still, its IPO exceeded expectations, opening at $21 a share and closing above $32 on the first day.

“I think that just shows there’s a lot of hype on Wall Street around artificial intelligence-related ventures,” Hao said. “Fermi, in the four months since it announced itself as a company, has found a lot of different ways to grab people’s attention.”

For now, the project represents both a technological gamble and a test of investor faith — a fusion of nuclear ambition and AI optimism that has Wall Street watching closely.

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Global Coal Power Decline 2019 signals a record fall in coal-fired electricity as China plateaus, India dips, and the EU and US accelerate renewables, curbing carbon emissions and advancing the global energy transition.

Key Points

A record 2019 drop in global coal power as renewables rise and demand slows across China, India, the EU, and the US.

✅ 3% global fall in coal-fired electricity in 2019.

✅ China plateaus; India declines for first time in decades.

✅ EU and US shift to renewables and gas, cutting emissions.

The world’s use of coal-fired electricity is on track for its biggest annual fall on record this year after more than four decades of near-uninterrupted growth that has stoked the global climate crisis.

Data shows that coal-fired electricity is expected to fall by 3% in 2019, or more than the combined coal generation in Germany, Spain and the UK last year and could help stall the world’s rising carbon emissions this year.

The steepest global slump on record is likely to emerge in 2019 as India’s reliance on coal power falls for the first time in at least three decades this year, and China’s coal power demand plateaus, reflecting the broader global energy transition underway.

Both developing nations are using less coal-fired electricity due to slowing economic growth in Asia as well as the rise of cleaner energy alternatives. There is also expected to be unprecedented coal declines across the EU and the US as developed economies turn to clean forms of energy such as low-cost solar power to replace ageing coal plants.

In almost 40 years the world’s annual coal generation has fallen only twice before: in 2009, in the wake of the global financial crisis, and in 2015, following a slowdown in China’s coal plants amid rising levels of deadly air pollution.

The research was undertaken by the Centre for Research on Energy and Clean Air , the Institute for Energy Economics and Financial Analysis and the UK climate thinktank Sandbag.

The researchers found that China’s coal-fired power generation was flatlining, despite an increase in the number of coal plants being built, because they were running at record low rates. China builds the equivalent of one large new coal plant every two weeks, according to the report, but its coal plants run for only 48.6% of the time, compared with a global utilisation rate of 54% on average.

The findings come after a report from Global Energy Monitor found that the number of coal-fired power plants in the world is growing, because China is building new coal plants five times faster than the rest of the world is reducing their coal-fired power capacity.

The report found that in other countries coal-fired power capacity fell by 8GW in the 18 months to June but over the same period China increased its capacity by 42.9GW.

In a paper for the industry journal Carbon Brief, the researchers said: “A 3% reduction in power sector coal use could imply zero growth in global CO2 emissions, if emissions changes in other sectors mirror those during 2018.”

However, the authors of the report have warned that despite the record coal power slump the world’s use of coal remained far too high to meet the climate goals of the Paris agreement, and some countries are still seeing increases, such as Australia’s emissions rise amid increased pollution from electricity and transport.

The US – which is backing out of the Paris agreement – has made the deepest cuts to coal power of any developed country this year by shutting coal plants down in favour of gas power and renewable energy, with utilities such as Duke Energy facing investor pressure to disclose climate plans. By the end of August the US had reduced coal by almost 14% over the year compared with the same months in 2018.

The EU reported a record slump in coal-fired electricity use in the first half of the year of almost a fifth compared with the same months last year. This trend is expected to accelerate over the second half of the year to average a 23% fall over 2019 as a whole. The EU is using less coal power in favour of gas-fired electricity – which can have roughly half the carbon footprint of coal – and renewable energy, helped by policies such as the UK carbon tax that have slashed coal-fired generation.

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Ontario Clean Electricity Regulations accelerate renewable energy adoption, drive emissions reduction, and modernize the smart grid with energy storage, efficiency targets, and reliability upgrades to support decarbonization and a stable power system for Ontario.

Key Points

Standards to cut emissions, grow renewables, improve efficiency, and modernize the grid with storage and smart systems.

✅ Phases down fossil generation and invests in storage.

✅ Sets utility efficiency targets to curb demand growth.

✅ Upgrades to smart grid for reliability and resiliency.

Ontario has taken a significant step forward in its energy transition with the introduction of new clean electricity regulations. These regulations, complementing federal Clean Electricity Regulations, aim to reduce carbon emissions, promote sustainable energy sources, and ensure a cleaner, more reliable electricity grid for future generations. This article explores the motivations behind these regulations, the strategies being implemented, and the expected impacts on Ontario’s energy landscape.

The Need for Clean Electricity

Ontario, like many regions around the world, is grappling with the effects of climate change, including more frequent and severe weather events. In response, the province has set ambitious targets to reduce greenhouse gas emissions and increase the use of renewable energy sources, reflecting trends seen in Alberta’s path to clean electricity across Canada. The electricity sector plays a central role in this transition, as it is responsible for a significant portion of the province’s carbon footprint.

For years, Ontario has been moving away from coal as a source of electricity generation, and now, with the introduction of these new regulations, the province is taking a step further in decarbonizing its grid, including its largest competitive energy procurement to date. By setting clear goals and standards for clean electricity, the province hopes to meet its environmental targets while ensuring a stable and affordable energy supply for all Ontarians.

Key Aspects of the New Regulations

The regulations focus on encouraging the use of renewable energy sources such as wind, solar, hydroelectric, and geothermal power. One of the key elements of the plan is the gradual phase-out of fossil fuel-based energy sources. This shift is expected to be accompanied by greater investments in energy storage solutions, including grid batteries, to address the intermittency issues often associated with renewable energy sources.

Ontario’s new regulations also emphasize the importance of energy efficiency in reducing overall demand. As part of this initiative, utilities and energy providers will be required to meet strict energy-saving targets and participate in new electricity auctions designed to reduce costs, ensuring that both consumers and businesses are incentivized to use energy more efficiently.

In addition, the regulations promote technological innovation in the electricity sector. By supporting the development of smart grids, energy storage technologies, and advanced power management systems, Ontario is positioning itself to become a leader in the global energy transition.

Impact on the Economy and Jobs

One of the anticipated benefits of the clean electricity regulations is their positive impact on Ontario’s economy. As the province invests in renewable energy infrastructure and clean technologies, new job opportunities are expected to arise in industries such as manufacturing, construction, and research and development. These regulations also encourage innovation in energy services, which could lead to the growth of new companies and industries, while easing pressures on industrial ratepayers through complementary measures.

Furthermore, the transition to cleaner energy is expected to reduce the long-term costs associated with climate change. By investing in sustainable energy solutions now, Ontario will help mitigate the financial burdens of environmental damage and extreme weather events in the future.

Challenges and Concerns

While the new regulations have been widely praised for their environmental benefits, they are not without their challenges. One of the primary concerns is the potential cost to consumers, and some Ontario hydro policy critique has called for revisiting legacy pricing approaches to improve affordability. While renewable energy sources have become more affordable over the years, transitioning from fossil fuels could still result in higher electricity prices in the short term. Additionally, the implementation of new technologies, such as smart grids and energy storage, will require substantial upfront investment.

Moreover, the intermittency of renewable energy generation poses a challenge to grid stability. Ontario’s electricity grid must be able to adapt to fluctuations in energy supply as more variable renewable sources come online. This challenge will require significant upgrades to the grid infrastructure and the integration of storage solutions to ensure reliable energy delivery.

The Road Ahead

Ontario’s clean electricity regulations represent an important step in the province’s commitment to combating climate change and transitioning to a sustainable, low-carbon economy. While there are challenges to overcome, the benefits of cleaner air, reduced emissions, and a more resilient energy system will be felt for generations to come. As the province continues to innovate and lead in the energy sector, Ontario is positioning itself to thrive in the green economy of the future.

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Ofgem Renewables Obligations drive supplier payments for renewables fees, feed-in tariffs, and renewable generation, with non-payment risking supply licences amid the price cap and volatile wholesale prices across the UK energy market.

Key Points

Mandatory payments by suppliers funding renewables via feed-in tariffs; non-payment can trigger supply licence revoking.

✅ Covers Renewables Obligation and Feed-in Tariff scheme compliance.

✅ Non-payment can lead to Ofgem action and licence loss.

✅ Affected by price cap and wholesale price volatility.

Seven small British energy suppliers owe a total of 34 million pounds ($43.74 million) in renewables fees, amid a renewables backlog that has stalled projects, and could face losing their supply licences if they cannot pay, energy regulator Ofgem reports.

Under Britain’s energy market rules, suppliers of energy must meet so-called renewables obligations and feed-in tariffs, including households' ability to sell solar power back to energy firms, which are imposed on them by the government to help fund renewable power generation.

Several small energy companies have gone bust over the past two years, a trend echoed by findings from a global utility study on renewable priorities, as they struggled to pay the renewables fees and as their profits were affected by a price cap on the most commonly used tariffs and fluctuating wholesale prices, even as a 10 GW contract brings new renewable capacity onto the UK grid.

Ofgem has called on the companies to make necessary payments by Oct. 31, as moves to offer community-generated power to all UK customers progress.

“If they do not pay Ofgem could start the process of revoking their licences to supply energy,” it said in a statement, as offshore wind power continues to scale nationwide.

The seven suppliers are, amid debates over clean energy impacts, Co-Operative Energy Limited; Flow Energy Limited; MA Energy Limited; Nabuh Energy Limited; Robin Hood Energy Limited; Symbio Energy Limited and Tonik Energy Limited. ($1 = 0.7773 pounds)

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Ontario Hydro Rate Relief Plan delivers short-term electricity bill cuts, while leaked cabinet forecasts show inflation-linked hikes, borrowing costs, and a Clean Energy Adjustment under the province's long-term energy plan.

Key Points

A provincial plan that cuts bills now but defers costs, projecting rate hikes and adding a Clean Energy Adjustment.

✅ 25% cut now, after 8% HST relief; extra 17% reduction applied.

✅ Forecast: inflation-linked hikes later; borrowing adds long-term costs.

✅ Clean Energy Adjustment line to repay deferred system costs.

The short-term gain of a 25 per cent hydro rate cut this summer could lead to long-term pain as a leaked cabinet document forecasts prices jumping again in five years.

In the briefing materials leaked and obtained by the Progressive Conservatives, rates will start rising 6.5 per cent a year in 2022 and top out at 10.5 per cent in 2028, when average monthly bills hit $215.

That would be up from $123 this year once the rate cut — the subject of long-awaited legislation to lower electricity rates unveiled Thursday by Energy Minister Glenn Thibeault — takes full effect. There will be another 17-per-cent cut in addition to the 8 per cent taken off bills in January when the provincial portion of the HST was waived.

The leaked papers overshadowed Thibeault’s efforts to tout the price break, which will be followed with four years of hydro rate increases at 2 per cent, roughly the rate of inflation.

Thibeault charged that the Conservatives used an “outdated” document to distract from the fact that they are the only major party without a plan for dealing with skyrocketing hydro rates, with a year to go until next June’s provincial election.

“It’s not a coincidence,” he told reporters, denying any plans for an eventual 10.5-per-cent rate hike and promising the government’s new long-term energy plan, due in a few months, will have better numbers.

“We are working hard right now to continue to pull costs out of the system.”

Opposition parties said the Liberal plan doesn’t deal with the underlying problems that have made electricity expensive and simply borrows money to spread the costs over a longer period of time, with $25 billion in interest charges over 30 years.

Some observers also noted that a deal with Quebec would not reduce hydro bills, highlighting concerns about lasting affordability.

“The price of electricity is going to skyrocket after the next election,” warned Conservative MPP Todd Smith (Prince Edward—Hastings).

“The government isn’t being honest with the people of Ontario when it comes to the price of electricity.”

The documents show average monthly bills peaking at $231 in the year 2047, before falling back to $210 the following year once the 30 years of interest payments are over.

Conservative sources say they obtained the papers stamped “confidential cabinet document” from a whistleblower after Thibeault’s rate cut plan was presented to cabinet ministers at a meeting in early March.

There is no date on the document, which the energy minister alternately dismissed as “inaccurate” or possibly one of many that have been prepared with different options in mind.

“We’ve had hundreds of briefings with hundreds of documents … I can’t comment on one graph when we’ve been looking at hundreds of scenarios.”

New Democrats, who have proposed a scheme to cut rates, if elected, also called the government plan an election ploy with Liberals lagging in the polls.

“We’re going to take on a huge debt so (Premier) Kathleen Wynne can look good on the hustings in the next few months, and for decades we’re going to pay for it,” said MPP Peter Tabuns (Toronto-Danforth).

Thibeault acknowledged the Liberal plan will start repaying borrowed money in the mid- or late 2020s and it will show up separately on hydro bills as the “Clean Energy Adjustment”, a kind of electricity recovery rate that could raise costs.

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AI Load Forecasting for Utilities leverages machine learning, smart meters, and predictive analytics to balance energy demand during COVID-19 disruptions, optimize grid reliability, support demand response, and stabilize rates for residential and commercial customers.

Key Points

AI predicts utility demand with ML and smart meters to improve reliability and reduce costs.

✅ Adapts to rapid demand shifts with accurate short term forecasts

✅ Optimizes demand response and distributed energy resources

✅ Reduces outages risk while lowering procurement and operating costs

The spread of the novel coronavirus that causes COVID-19 has prompted state and local governments around the U.S. to institute shelter-in-place orders and business closures. As millions suddenly find themselves confined to their homes, the shift has strained not only internet service providers, streaming platforms, and online retailers, but the utilities supplying power to the nation’s electrical grid, which face longer, more frequent outages as well.

U.S. electricity use on March 27, 2020 was 3% lower than it was on March 27, 2019, a loss of about three years of sales growth. Peter Fox-Penner, director of the Boston University Institute for Sustainable Energy, asserted in a recent op-ed that utility revenues will suffer because providers are halting shutoffs and deferring rate increases. Moreover, according to research firm Wood Mackenzie, the rise in household electricity demand won’t offset reduced business electricity demand, mainly because residential demand makes up just 40% of the total demand across North America.

Some utilities are employing AI and machine learning for the energy transition to address the windfalls and fluctuations in energy usage resulting from COVID-19. Precise load forecasting could ensure that operations aren’t interrupted in the coming months, thereby preventing blackouts and brownouts. And they might also bolster the efficiency of utilities’ internal processes, leading to reduced prices and improved service long after the pandemic ends.

Innowatts
Innowatts, a startup developing an automated toolkit for energy monitoring and management, counts several major U.S. utility companies among its customers, including Portland General Electric, Gexa Energy, Avangrid, Arizona Public Service Electric, WGL, and Mega Energy. Its eUtility platform ingests data from over 34 million smart energy meters across 21 million customers in more than 13 regional energy markets, while its machine learning algorithms analyze the data to forecast short- and long-term loads, variances, weather sensitivity, and more.

Beyond these table-stakes predictions, Innowatts helps evaluate the effects of different rate configurations by mapping utilities’ rate structures against disaggregated cost models. It also produces cost curves for each customer that reveal the margin impacts on the wider business, and it validates the yield of products and cost of customer acquisition with models that learn the relationships between marketing efforts and customer behaviors (like real-time load).

Innowwatts told VentureBeat that it observed “dramatic” shifts in energy usage between the first and fourth weeks of March. In the Northeast, “non-essential” retailers like salons, clothing shops, and dry cleaners were using only 35% as much energy toward the end of the month (after shelter-in-place orders were enacted) versus the beginning of the month, while restaurants (excepting pizza chains) were using only 28%. In Texas, conversely, storage facilities were using 142% as much energy in the fourth week compared with the first.

Innowatts says that throughout these usage surges and declines, its clients took advantage of AI-based load forecasting to learn from short-term shocks and make timely adjustments. Within three days of shelter-in-place orders, the company said, its forecasting models were able to learn new consumption patterns and produce accurate forecasts, accounting for real-time changes.

Innowatts CEO Sid Sachdeva believes that if utility companies had not leveraged machine learning models, demand forecasts in mid-March would have seen variances of 10-20%, significantly impacting operations.

“During these turbulent times, AI-based load forecasting gives energy providers the ability to … develop informed, data-driven strategies for future success,” Sachdeva told VentureBeat. “With utilities and energy retailers seeing a once-in-a-lifetime 30%-plus drop in commercial energy consumption, accurate forecasting has never been more important. Without AI tools, utilities would see their forecasts swing wildly, leading to inaccuracies of 20% or more, placing an enormous strain on their operations and ultimately driving up costs for businesses and consumers.”

Autogrid
Autogrid works with over 50 customers in 10 countries — including Energy Australia, Florida Power & Light, and Southern California Edison — to deliver AI-informed power usage insights. Its platform makes 10 million predictions every 10 minutes and optimizes over 50 megawatts of power, which is enough to supply the average suburb.

Flex, the company’s flagship product, predicts and controls tens of thousands of energy resources from millions of customers by ingesting, storing, and managing petabytes of data from trillions of endpoints. Using a combination of data science, machine learning, and network optimization algorithms, Flex models both physics and customer behavior, automatically anticipating and adjusting for supply and demand patterns through virtual power plants that coordinate distributed assets.

Autogrid also offers a fully managed solution for integrating and utilizing end-customer installations of grid batteries and microgrids. Like Flex, it automatically aggregates, forecasts, and optimizes capacity from assets at sub-stations and transformers, reacting to distribution management needs while providing capacity to avoid capital investments in system upgrades.

Autogrid CEO Dr. Amit Narayan told VentureBeat that the COVID-19 crisis has heavily shifted daily power distribution in California, where it’s having a “significant” downward impact on hourly prices in the energy market. He says that Autogrid has also heard from customers about transformer failures in some regions due to overloaded circuits, which he expects will become a problem in heavily residential and saturated load areas during the summer months (as utilities prepare for blackouts across the U.S. when air conditioning usage goes up).

“In California, [as you’ll recall], more than a million residents faced wildfire prevention-related outages in PG&E territory in 2019,” Narayan said, referring to the controversial planned outages orchestrated by Pacific Gas & Electric last summer. “The demand continues to be high in 2020 in spite of the COVID-19 crisis, as residents prepare to keep the lights on and brace for a similar situation this summer. If a 2019 repeat happens again, it will be even more devastating, given the health crisis and difficulty in buying groceries.”

AI making a difference
AI and machine learning isn’t a silver bullet for the power grid — even with predictive tools at their disposal, utilities are beholden to a tumultuous demand curve and to mounting climate risks across the grid. But providers say they see evidence the tools are already helping to prevent the worst of the pandemic’s effects — chiefly by enabling them to better adjust to shifted daily and weekly power load profiles.

“The societal impact [of the pandemic] will continue to be felt — people may continue working remotely instead of going into the office, they may alter their commute times to avoid rush hour crowds, or may look to alternative modes of transportation,” Schneider Electric chief innovation officer Emmanuel Lagarrigue told VentureBeat. “All of this will impact the daily load curve, and that is where AI and automation can help us with maintenance, performance, and diagnostics within our homes, buildings, and in the grid.”

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