In this week's episode, we explore a tale of two very different eastern power grids: PJM and ISO New England.

For years, PJM's interconnection queue was hopelessly snarled, with the grid operator getting overwhelmed by small renewable projects and speculative developers. Project reviews were taking five to seven years under a "first-come, first-served" model, leading to massive delays and withdrawn projects.

Now, PJM has overhauled its process to a "first-ready, first-served" approach, requiring developers to provide meaningful upfront financial commitments and proof of site control. The results of their latest application window are staggering: PJM recently announced 220 gigawatts (220,000 MW) of proposed capacity across 811 new projects.

Watch to learn more about:

The new PJM fuel mix: Why gas-fired generation (106 GW) and battery storage (66 GW) are leading the queue, alongside a surprising 27 nuclear projects.

Google's AI grid intervention: How PJM is deploying Tapestry’s HyperQ AI software to expedite the review of these massive data sets.

The "Phantom Load" problem: Why speculative queue behavior is inflating capacity numbers for new data centers by an estimated 3 to 10 times.

The supply chain reality check: Why much of this approved supply won't come online soon, as gas turbines are sold out through 2030 and projects like Commonwealth Fusion don't even have a working reactor yet.

The New England contrast: Why ISO New England is facing the exact opposite scenario, having recently downgraded its load growth forecast to just 9% through 2035 due to a lack of data centers and slowing EV and heat pump sales.

Finally, we discuss the unpredictable wildcards in grid forecasting. If the ongoing conflict in the Strait of Hormuz triggers an enormous petroleum price shock, New Englanders paying over $500 for 100 gallons of heating oil will race for heat pumps, instantly altering these long-term projections.

In a world where everything is constantly in flux, the only thing grid planners can truly count on is the accelerating pace of change. Watch now to understand the regionally differentiated reality of our power grid!

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🎙️ About Energy Future: Powering Tomorrow’s Cleaner World

Hosted by Peter Kelly-Detwiler, Energy Future explores the trends, technologies, and policies driving the global clean-energy transition — from the U.S. grid and renewable markets to advanced nuclear, fusion, and EV innovation.

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Greetings from Mexico!
In this episode, we dive deep into a fascinating new metric called the Compute Heat Rate (CHR) and explore its potentially profound implications for the future of electricity prices and the power grid
.
With the explosive growth of AI, power grids are facing unprecedented demands. For example, Texas's ERCOT grid operator recently projected that load could max out at a staggering 319,650 megawatts by 2030, driven largely by data centers
. We are already seeing the impact in markets like PJM, where data load growth has blown up capacity revenues to the tune of an estimated $23 billion in costs over the next three years
.
But what happens to the actual energy prices? That is what the CHR attempts to answer by asking: at what price would data centers elect NOT to consume power?
Introduced by industry veteran Hans Royal, the CHR measures the maximum electricity price a data center operator can rationally pay before their computing tasks become uneconomic
. Because AI creates enormous economic value, these data centers are incredibly inflexible and willing to pay massive premiums for power
. While traditional large loads like steel or aluminum producers will typically shut down when prices hit $40 to $120 per megawatt hour
, Royal estimates that AI data centers have a blended CHR of approximately 6,350permegawatthour
.Forhighlycritical,just−in−timeAIinferenceservices,theymightnotcurtailpoweruntilpriceshitover∗∗53,000 per megawatt hour**!
Watch to learn more about:
The massive gap between AI load forecasts and grid realities
.
Why regulators are demanding "Flex Mosaic" and load-shifting capabilities from data centers
.
The difference between Large Language Model (LLM) training loads and peaky inference loads
.
How the incredible power density of new tech—like the Nvidia Rubin architecture, where a fridge-sized box uses the power of 65 households—could price regular consumers out of the market
.
If these data centers refuse to curtail power at any normal wholesale price, we could see massive localized demand supply imbalances
. Watch now to understand the new metric tracking this emerging grid crisis

Support the show

🎙️ About Energy Future: Powering Tomorrow’s Cleaner World

Hosted by Peter Kelly-Detwiler, Energy Future explores the trends, technologies, and policies driving the global clean-energy transition — from the U.S. grid and renewable markets to advanced nuclear, fusion, and EV innovation.

💡 Stay Connected
Subscribe wherever you listen — including Spotify, Apple Podcasts, Amazon Music, and YouTube.

🌎 Learn More
Visit peterkellydetwiler.com
for weekly market insights, in-depth articles, and energy analysis.

Is it now AI's world, and we just live—and pay for electricity—in it? The AI revolution requires a staggering amount of electricity, and our power grid is struggling to keep up with the astonishingly rapid growth of data centers.

In this video, we dive into the unprecedented crisis facing grid operators like PJM Interconnection. With some regions seeing data-related energy loads jump from just 600 megawatts to 11,000 megawatts, grid operators are facing challenges never seen before in power markets.

Key topics covered in this video:

The Data Center Explosion: How utilities at ground zero, like Dominion in Virginia, are fielding up to 70,000 megawatts of large load interconnection requests—nearly equal to or exceeding the load they currently serve.

PJM’s "Hail Mary" Solution: A breakdown of PJM’s proposed parallel auction, a one-off bilateral contracting process aiming to secure 14,900 megawatts of new capacity by matching large loads with supply owners.

Supply Chain Roadblocks: Why finding enough equipment is a major hurdle, with grid-scale gas turbines essentially sold out globally through 2029.

A Broken Market: How the massive wealth of tech giants is warping energy economics. With data centers valuing early grid connection at up to $7 billion per gigawatt, capital is practically guaranteed to abandon the standard, price-capped public power markets in favor of lucrative, uncapped bilateral tech contracts.

As energy developers chase higher returns to power the AI boom, existing resources are being locked out, and everyday consumers might face the collateral impacts. Watch to understand why fixing the grid for AI is a nearly impossible puzzle.

Support the show

🎙️ About Energy Future: Powering Tomorrow’s Cleaner World

Hosted by Peter Kelly-Detwiler, Energy Future explores the trends, technologies, and policies driving the global clean-energy transition — from the U.S. grid and renewable markets to advanced nuclear, fusion, and EV innovation.

💡 Stay Connected
Subscribe wherever you listen — including Spotify, Apple Podcasts, Amazon Music, and YouTube.

🌎 Learn More
Visit peterkellydetwiler.com
for weekly market insights, in-depth articles, and energy analysis.