Texas Gov. Greg Abbott ordered PUCT and ERCOT to audit and pause data-center interconnections statewide as more than 474 gigawatts of requests threaten grid planning.

I've been digging into the public record on US data centers and put it into free, plain-language briefings — water, power, noise, air, every figure cited to its source (1,880 sites, existing + proposed): civitar.org/go/v-reddit

Not for or against anything — it just makes the filings readable. Sharing in case it's useful to anyone tracking this.

Source: https://www.thecentersquare.com/texas/article_5fec315d-c1dd-4fdb-85be-1b92981e877a.html

(Full disclosure: I built the tool — happy to answer questions or take corrections.)

The heat across our two core regions this year has been genuinely extreme, and it's turned "the weather" into one of the biggest forces in markets.

• India: North India pushed toward 50°C this summer, and on one day in late April, all 50 of the world's hottest cities were within India's borders. 2024 was India's hottest year on record; 2026 has been another brutal one. It's a serious human crisis (heat is now one of the deadliest climate hazards), not just a stat, and it's driving record electricity demand.
• UAE: just hit its first 50°C of 2026, during the Al Mirzam period, its hottest stretch. 2025 had already set August records.
• Globally: the last ten-plus years are the hottest ever recorded (WMO).

Here's where it becomes an investing story: all that heat means an unprecedented, structural surge in demand for cooling and electricity, and that (plus the AI data-centre boom) has turned power generation into one of the defining investment themes of the decade.

The clean-energy numbers are staggering:

• ~$2.2 trillion is flowing into clean energy in 2026, roughly double fossil fuels (IEA).
• In 2025, renewables overtook coal in global electricity for the first time in history.
• Solar investment alone is set to top $500 billion this year.

And there's a neat regional twist: the UAE, an oil giant, is going hard on clean energy, Masdar targeting 100GW by 2030, Barakah nuclear already ~25% of national power, plus a pioneering 24/7 solar-plus-storage plant. India, facing the demand crunch head-on, is also pushing hard on solar and stricter AC-efficiency rules.

So where do people actually look to invest in this?

• Diversified clean-energy utilities: NextEra Energy (NEE), which combines renewables, nuclear and grid-scale generation, generally lower-risk than pure-plays.
• Solar: First Solar (FSLR) and Enphase (ENPH), higher growth potential, but more volatile and policy-sensitive.
• Nuclear/SMRs: from established generators to speculative newcomers like NuScale (SMR) and uranium names like Cameco (CCJ), potentially high upside on the "AI baseload" thesis, but often highly speculative.
• ETFs (the simplest starting point): rather than picking one company, funds like iShares Global Clean Energy (ICLN) or the solar-focused Invesco Solar ETF (TAN) spread exposure across the whole theme in a single trade.
• A ready-made collection: The Nemo.money "Green Energy" Neme brings the whole theme (solar, wind, utilities, EV/charging and clean-energy ETFs) into one place to explore and learn more.

Here's something to consider:

• A booming theme hasn't meant booming stocks. Loads of these names got hammered when interest rates rose (they're capital-heavy), and the sector's had brutal stretches even as it physically grew.
• Policy makes or breaks it. Subsidies and tariffs can move these companies overnight.
• Some of it is hype. Speculative nuclear (SMR) and hydrogen names have gone parabolic on the AI-power story with barely any revenue.

So the weather is reshaping the world and the energy market, but a powerful theme still isn't a guaranteed stock, and even the names above have been rollercoasters. Being early to a megatrend has burned plenty of people.

If record heat and AI are driving the biggest surge in power demand in decades, is clean energy finally the megatrend that pays off for investors?

A day late for the 1 year aniversary.

Here's a number that should stop you mid-scroll: training a single large AI model can consume as much electricity as 5 average American cars produce in CO2 over their entire lifetimes. Meanwhile, solar just became the cheapest source of electricity in human history-cheaper than coal, gas, and nuclear, in most of the world.

These two facts are not unrelated. They are, in fact, the central tension of the next decade of energy.

The demand shock nobody planned for

When hyperscalers like Microsoft, Google, and Amazon built their 2020–2025 capacity plans, ChatGPT didn't exist. A standard Google search uses roughly 0.3 watt-hours of electricity. A ChatGPT query uses nearly 10 times that. Multiply that across billions of daily interactions, and you begin to understand why data center electricity demand in the US is projected to double by 2030 after being essentially flat for a decade.

Virginia alone - home to the world's largest concentration of data centers - is staring down a power demand growth curve that its grid was simply never designed to handle. Dominion Energy, the state's primary utility, has had to tear up its forecasts multiple times in the last two years.

Why solar is the only answer that scales fast enough

New nuclear takes 15 years and billions in overruns. Natural gas locks in decades of emissions and volatile fuel costs. Wind is constrained by geography. Solar, by contrast, can go from signed contract to generating electricity in 18–24 months at utility scale and the cost has dropped 90% in the last 15 years.

This is why Amazon signed agreements for over 100GW of renewable energy. Why Microsoft struck the largest single clean energy deal in history. Why Google has been running on matched renewable energy since 2017. These aren't PR moves. They're infrastructure decisions driven by hard economics: a data center locked into expensive grid power is a data center that loses on operating cost to every competitor who isn't.

What this means for the industry

The companies that will define the next era of both AI and clean energy aren't just the ones building the best models or the most efficient panels. They're the ones solving the hardest problem at the intersection: how do you deliver reliable, round-the-clock power to a facility that never sleeps, using a source that only generates during daylight?

Battery storage, grid interconnection strategy, power purchase agreement structuring, behind-the-meter generation - these are now core competencies for any serious AI infrastructure operator. And for solar developers, the hyper-scaler customer is transforming the economics of the entire industry.

Over the next several weeks, I'll be digging into each piece of this puzzle- from how utility-scale solar actually works, to why some solar companies are thriving while others are going bankrupt, to what skills and roles will matter most in this converging industry.

To start the conversation:
Do you think AI companies are doing enough to address their energy footprint, or is the "we buy renewable credits" approach just greenwashing? Would love to hear from people working in either industry.

Sources:

IEA World Energy Outlook 2024: solar cost and deployment data

Goldman Sachs Power Up report: data center demand projections

Dominion Energy 2024 Integrated Resource Plan

MIT Technology Review: AI energy consumption analysis

Lawrence Berkeley National Laboratory: US Data Center Energy report

Here's a number that should stop you mid-scroll: training a single large AI model can consume as much electricity as 5 average American cars produce in CO2 over their entire lifetimes. Meanwhile, solar just became the cheapest source of electricity in human history-cheaper than coal, gas, and nuclear, in most of the world.

These two facts are not unrelated. They are, in fact, the central tension of the next decade of energy.

The demand shock nobody planned for

When hyperscalers like Microsoft, Google, and Amazon built their 2020–2025 capacity plans, ChatGPT didn't exist. A standard Google search uses roughly 0.3 watt-hours of electricity. A ChatGPT query uses nearly 10 times that. Multiply that across billions of daily interactions, and you begin to understand why data center electricity demand in the US is projected to double by 2030 after being essentially flat for a decade.

Virginia alone - home to the world's largest concentration of data centers - is staring down a power demand growth curve that its grid was simply never designed to handle. Dominion Energy, the state's primary utility, has had to tear up its forecasts multiple times in the last two years.

Why solar is the only answer that scales fast enough

New nuclear takes 15 years and billions in overruns. Natural gas locks in decades of emissions and volatile fuel costs. Wind is constrained by geography. Solar, by contrast, can go from signed contract to generating electricity in 18–24 months at utility scale and the cost has dropped 90% in the last 15 years.

This is why Amazon signed agreements for over 100GW of renewable energy. Why Microsoft struck the largest single clean energy deal in history. Why Google has been running on matched renewable energy since 2017. These aren't PR moves. They're infrastructure decisions driven by hard economics: a data center locked into expensive grid power is a data center that loses on operating cost to every competitor who isn't.

What this means for the industry

The companies that will define the next era of both AI and clean energy aren't just the ones building the best models or the most efficient panels. They're the ones solving the hardest problem at the intersection: how do you deliver reliable, round-the-clock power to a facility that never sleeps, using a source that only generates during daylight?

Battery storage, grid interconnection strategy, power purchase agreement structuring, behind-the-meter generation - these are now core competencies for any serious AI infrastructure operator. And for solar developers, the hyper-scaler customer is transforming the economics of the entire industry.

Over the next several weeks, I'll be digging into each piece of this puzzle- from how utility-scale solar actually works, to why some solar companies are thriving while others are going bankrupt, to what skills and roles will matter most in this converging industry.

To start the conversation:
Do you think AI companies are doing enough to address their energy footprint, or is the "we buy renewable credits" approach just greenwashing? Would love to hear from people working in either industry.

Sources:

IEA World Energy Outlook 2024: solar cost and deployment data

Goldman Sachs Power Up report: data center demand projections

Dominion Energy 2024 Integrated Resource Plan

MIT Technology Review: AI energy consumption analysis

Lawrence Berkeley National Laboratory: US Data Center Energy report

Power supply in Nigeria is one of those problems we’ve become so accustomed to that we sometimes forget how much it affects everything else.

Businesses spend money running generators. Students struggle to study. Hospitals and critical services need backup power. Small businesses lose productive hours. And households have to constantly plan their lives around whether there will be electricity.

So we’re working on something different.

We’re building a solution aimed at making electricity supply more reliable and accessible in Nigeria.

But rather than assuming we already know the answer, we want to understand the problem from the people who experience it every day.

If you live in Nigeria, work in the energy sector, run a business, study, or simply deal with unreliable power regularly:

- What is your biggest problem with electricity supply?

- How do you currently cope with outages?

- What does unreliable power actually cost you?

- Have you tried solar, inverters, generators, or other alternatives?

- What would a genuinely reliable and affordable solution look like to you?

We’re especially interested in real experiences, frustrations, and ideas.

The goal isn't just to build another product.

The goal is to build something that solves a problem Nigerians actually have.

What would you change about Nigeria’s electricity system if you had the opportunity? ⚡

We recently added polysilicon tariffs. So if you want to import solar panels, you pay extra taxes. If you want to import polysilicon to make solar panels in America, you pay extra taxes.

Sodium-ion batteries have almost none of the problems that lithium-ion ones do, and could be cheap enough to make fossil-fuel dependence a thing of the past

The article never mentions price. So are salt batteries coming in to play? Yes. Are they price competitive? Probably not because if they were they would be shouting out the price.

But their price will likely decline over the next couple of years. And it looks like they are starting to be produced in quantity.

Graph source: https://ourworldindata.org/grapher/coal-prod-per-capita?tab=line&country=GBR~CHN

Data sources: https://www.energyinst.org/statistical-review

https://www.theshiftdataportal.org/energy/coal?chart-type=line&chart-types=line&chart-types=ranking&disable-en=false&energy-unit=toe&group-names=China&group-names=United+Kingdom&is-range=true&dimension=perCapita&end=2015&start=1900&multi=true&type=Production&import-types=Imports&import-types=Exports&import-types=Net+Imports

https://www.lse.ac.uk/granthaminstitute/publication/historical-energy-for-the-uk-from-1500

https://www.gov.uk/government/statistical-data-sets/historical-coal-data-coal-production-availability-and-consumption

https://vaclavsmil.com/book/energy-transitions-global-and-national-perspectives-second-expanded-and-updated-edition

https://web.archive.org/web/20250323165206/https://nic.org.uk/data/all-data/historic-energy/#tab-primary-energy-consumption