Southeastern utilities are now projecting some of the most aggressive growth rates tied to data centers. History suggests caution is warranted—especially when ratepayers bear the financial risk.
The AI revolution is undeniably reshaping our digital landscape, but a crucial question remains: how will we power it? In his thought-provoking new paper, “Artificial Intelligence Meets Natural Stupidity: Managing the Risks,” energy expert Amory Lovins presents a sobering analysis that challenges many of the prevailing narratives around AI and energy, with particular implications for the Southeastern United States.
Amory Lovins
The AI-Driven Electricity Bubble Risk
Lovins identifies a potential trillion-dollar overbuild in AI infrastructure, driven by speculative investments and highly uncertain projections. Despite the hype, AI’s future electricity needs remain wildly unpredictable, influenced by:
- Rapidly evolving technology (efficiency quadruples roughly each year)
- Uncertain market adoption
- Volatile market conditions
- Limited trust in AI systems
This scenario bears a striking resemblance to the 1999 IT-driven electricity boom, when the coal industry claimed information technology would require half the nation’s electricity by 2020. That prediction proved spectacularly wrong, resulting in hundreds of unnecessary power plants that hurt investors.
The Reality Check: A Southeastern Focus
Before we commit to building massive new power infrastructure, consider these facts:
- Current Usage: Data centers currently use only about 4-5% of US electricity and 1.5% of global electricity
- AI Portion: Of that data center usage, only about a quarter powers AI
- 2023-2024 Trends: US grid electricity fell in 2023 and rose just 2% in 2024 (the fourth-fastest rate in the past decade)
- Data Centers’ Share: Data centers’ share of US electricity crept up from just 4.4% to 4.5%
Here in the Southeast, we’re seeing particularly aggressive growth projections. In Georgia, data centers are driving a remarkable 80% of Georgia Power’s projected power sales growth through 2028. This dramatic forecast has prompted concerns from five major tech companies who challenged these projections in 2024. Despite these concerns, Georgia has already approved approximately $3 billion in new fossil-fueled power plants to meet this speculative demand.
Lovins emphasizes that while electricity growth is real in a few hotspots (like Northern Virginia’s “Data Center Alley” and increasingly in parts of Georgia), this pattern has been widely misreported as a national trend. The Southeast is becoming a key battleground for these competing narratives about energy needs.
Who Bears the Risk? Southeastern Ratepayers in the Crosshairs
Perhaps the most concerning aspect of this AI power rush is who ultimately bears the financial risk when projections don’t materialize. Lovins’ paper highlights a critical issue that directly affects Southeastern utility customers: ratepayer risk.
When utilities build new power plants for data centers that either don’t materialize or fail to remain operational long-term, existing customers often get stuck with the bill. Three major US credit-rating agencies warned in 2024 that utilities face “substantial credit risk” from inaccurate load forecasts, noting there is “a considerable risk that residential [and other non-data-center] customers may end up paying disproportionately.”
This risk is particularly acute in the Southeast:
- Georgia: Ratepayers could be on the hook for $3 billion in new fossil-fueled power plants that may not be needed if AI growth projections prove exaggerated
- Virginia: An independent state study found household electric bills could rise $14-37/month by 2040 due to AI-related infrastructure, with a 15% rise (averaging $22/month) already proposed
- Regional Impact: Across the Southeast, data center developers often secure favorable rates through “economic development” discounts, with lost revenue made up by other customers
As Lovins points out, this risk transfer is particularly concerning given that tech firms seeking these rate benefits hardly need financial assistance: “The Magnificent Seven in March 2025 had nearly five times the market capitalization of America’s hundred biggest shareholder-owned utilities combined.”
A local parallel can be drawn to past energy infrastructure projects in our region that didn’t pan out as projected, leaving ratepayers bearing costs for generations.
The Renewable Solution in the Southeast
Contrary to the narrative that only traditional power sources can meet AI’s demands, Lovins presents compelling evidence that renewables—particularly solar power—are actually ideal for powering AI data centers:
- Speed: Solar uniquely matches AI’s rapid development pace
- Flexibility: Can be deployed almost anywhere
- Reliability: When properly implemented with storage, provides highly reliable power
- Cost-effectiveness: Offers competitive pricing without the long-term risks
This is particularly relevant for the Southeast, which has excellent solar resources. According to Lovins’ analysis, “solar power uniquely matches AI’s torrid pace; can go about anywhere; would need zero land-use to power the world; and is readily integrated with other resources to provide cost-effective, clean, firm, critical-uses supply.”
The potential for renewable solutions in our region is substantial. Lovins notes that “in 2023, 60 countries or territories were 50–100% powered by wind, sun, and water—12 of those 98.4–100%—while 11 US states produced 53.2–118% as much electricity from those sources as all the electricity they used.” While the Southeast has historically lagged in renewable adoption, the economic case is becoming increasingly compelling.
Major tech companies seem to recognize this reality, having already contracted for approximately 40 GW of renewable energy for their data centers. In the Southeast, we’re starting to see examples of the “Power Couple” approach Lovins advocates—placing new data centers with renewable energy sources at underused gas plants—which could provide a model for future development.
The practical evidence can’t be ignored: Lovins cites Australia’s largest electricity user, mining giant Rio Tinto, which “just chose 2.7 GW of wind and solar, backed by 0.6+ GW of batteries” as “the cheapest and most reliable solution” to power its aluminum-smelting complex. If renewables can reliably power aluminum smelting—one of the most electricity-intensive industrial processes—they can certainly handle data centers.
The Efficiency Factor
One frequently overlooked aspect is AI’s potential to improve energy efficiency elsewhere. If AI can enhance building energy management, industrial processes, and transportation systems, it could potentially save more energy than its data centers consume.
However, Lovins cautions that we must also consider AI’s potential to accelerate fossil fuel extraction through improved exploration and production methods—possibly negating any efficiency benefits.
A Sensible Path Forward for Southeastern Utilities and Regulators
To navigate these complex challenges, Lovins suggests several approaches that have particular relevance for the Southeast:
- Risk Management: Require data center developers to guarantee power payments with bonds or insurance, ensuring ratepayers don’t bear the risk of project failures. As Lovins argues, “a sensible but apparently overlooked protection for the other customers…would be to require all promised payments to the utility for the large load’s new power supply to be bonded or insured by a creditworthy counterparty.” This approach would be especially valuable in states like Georgia, where large infrastructure investments are already planned.
- Demand Flexibility: Implement “flexiwatt” strategies that shift computing loads to times when clean energy is abundant. Lovins cites a February 2025 assessment concluding that such flexible data-center operations “could probably make existing power plants and grids sufficient to run all US data centers proposed for this decade.” This could be particularly effective in the Southeast, where peak demand often coincides with summer cooling needs.
- Co-location: Place new data centers with renewable energy sources at underused gas plants (“Power Couples”). Lovins notes that this approach “can neatly and profitably satisfy all the conflicting goals” of data center power needs. The Southeast has numerous natural gas facilities that could be ideal candidates for this approach.
- Market-Based Solutions: Let markets accurately price and allocate risks to the appropriate beneficiaries. Lovins notes that “if the risk of project failure is as small as developers claim, bonding should be very cheap.”
- Ratepayer Protection: Implement stronger regulatory oversight similar to Oregon’s approach, which makes large-load developers share forecasting risks, or enforce binding take-or-pay contracts as seen in Indiana, Michigan, and Ohio. Lovins points out that “some states hold other customers harmless by simple regulatory policies like Kentucky’s 35-year practice of forbidding rate discounts below cost, or beyond five years, or unless the utility has surplus capacity.”
For Southeastern utility commissions, these strategies offer practical ways to fulfill their mandate to protect consumers while still enabling economic development.
Conclusion: Protecting Southeastern Ratepayers While Embracing Innovation
As we navigate the AI era, the stakes for energy policy are particularly high in the Southeast. Poor bets on electricity demand could waste billions in investments, lock in unnecessary fossil fuel infrastructure, and—crucially for our region—burden ratepayers with decades of unnecessary rate increases from stranded assets.
The Southeast has historically been cautious about renewable energy adoption compared to some other regions, but the economics and reliability of these resources have improved dramatically. As Lovins points out, when properly understood and implemented, renewable energy solutions can now “neatly and profitably satisfy all the conflicting goals” of powering data centers reliably, affordably, and cleanly.
For Southeastern utilities and regulators, the key takeaway is clear: rather than rushing into massive infrastructure investments based on speculative projections, a more measured approach that accurately prices risk and protects ratepayers will better serve our communities. As Lovins concludes, “If the risk of project failure is as small as developers claim, bonding should be very cheap. If it’s not so small, it’s more important to avoid.”
By ensuring that tech companies bear the financial risks of their own growth projections through bonds or insurance requirements, we can welcome AI innovation while safeguarding our region’s economic interests.
With disciplined foresight, accurate risk pricing, and market-led investment in proven solutions, we can support AI’s development while avoiding repeating costly historical mistakes. The key lies in ensuring that AI’s energy foundation is as intelligent as the technology it powers—and that our region’s ratepayers don’t foot the bill for speculative investments.
This post is based on Amory Lovins’ May 2025 paper “Artificial Intelligence Meets Natural Stupidity: Managing the Risks.” The full paper provides extensive data and detailed analysis on these critical issues.
Resources
xAI Brings the “Move Fast and Break Things” Mindset to Memphis – SACE
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The post Southeastern States Face Ratepayer Risks in AI-Driven Energy Boom appeared first on SACE | Southern Alliance for Clean Energy.
Southeastern States Face Ratepayer Risks in AI-Driven Energy Boom
What would one expect a sycophant to say?
My maternal grandfather was born in southeastern Pennsylvania in 1903 and told me when I was a boy that in the 1920s, times were so good that saloon owners would offer a free lunch, consisting of bread and butter, cheese, cold cuts, pickles and the like. “Sure, they were hoping you’d buy a glass of beer for a nickel, but they really didn’t mind if you didn’t and simply scarfed down a free sandwich.”
He went on to tell me that nowadays, there’s a popular slogan: There’s no such thing as a free lunch, “but believe me, there was at the time.”
From today’s perspective of greed and selfishness, this whole story sounds like a fairy tale. Corporations and the congresspeople they own want one thing: to suck the life out of us.
Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage
This exclusive article originally appeared in PES Wind 4 – 2025 with the title, Operations take center stage in wind’s next chapter. It was written by Allen Hall and other members of the WeatherGuard Lightning Tech team.
As aging fleets, shrinking margins, and new policies reshape the wind sector, wind energy operations are in the spotlight. The industry’s next chapter will be defined not by capacity growth, but by operational excellence, where integrated, predictive maintenance turns data into decisions and reliability into profit.
Wind farm operations are undergoing a fundamental transformation. After hosting hundreds of conversations on the Uptime Wind Energy Podcast, I’ve witnessed a clear pattern: the most successful operators are abandoning reactive maintenance in favor of integrated, predictive strategies. This shift isn’t just about adopting new technologies; it’s about fundamentally rethinking how we manage aging assets in an era of tightening margins and expanding responsibilities.
The evidence was overwhelming at this year’s SkySpecs Customer Forum, where representatives from over 75% of US installed wind capacity gathered to share experiences and strategies. The consensus was clear: those who integrate monitoring, inspection, and repair into a cohesive operational strategy are achieving dramatic improvements in reliability and profitability.
Takeaway: These options have been available to wind energy operations for years; now, adoption is critical.
Why traditional approaches to wind farm operations are failing
Today’s wind operators face an unprecedented convergence of challenges. Fleets installed during the 2010-2015 boom are aging in unexpected ways, revealing design vulnerabilities no one anticipated. Meanwhile, the support infrastructure is crumbling; spare parts have become scarce, OEM support is limited, and insurance companies are tightening coverage just when operators need them most.
The situation is particularly acute following recent policy changes. The One Big Beautiful Bill in the United States has fundamentally altered the economic landscape. PTC farming is no longer viable; turbines must run longer and more reliably than ever before. Engineering teams, already stretched thin, are being asked to manage not just wind assets but solar and battery storage as well. The old playbook simply doesn’t work anymore.
Consider the scope of just one challenge: polyester blade failures. During our podcast conversation with Edo Kuipers of We4Ce, we learned that an estimated 30,000 to 40,000 blades worldwide are experiencing root bushing issues. ‘After a while, blades are simply flying off,’ Kuipers explained. The financial impact of a single blade failure can exceed €300,000 when you factor in replacement costs, lost production, and crane mobilization. Yet innovative repair solutions, like the one developed by We4Ce and CNC Onsite, can address the same problem for €40,000 if caught early. This pattern repeats across every major component. Gearbox failures that once required complete replacement can now be predicted months in advance. Lightning damage that previously caused catastrophic failures can be prevented with inexpensive upgrades and real-time monitoring. All these solutions are based on the principle that predicted maintenance is better than an expensive surprise.
Seeing problems before they happeny, and potential risks
The transformation begins with visibility. Modern monitoring systems reveal problems that traditional methods miss entirely. Eric van Genuchten of Sensing360 shared an eye-opening statistic on our podcast: ‘In planetary gearbox failures, they get 90%, so there’s still 10% of failures they cannot detect.’ That missing 10% represents the catastrophic failures that destroy budgets and production targets. Advanced monitoring technologies are filling these gaps. Sensing360’s fiber optic sensors, for example, detect minute deformations in steel components, revealing load imbalances and fatigue progression invisible to traditional monitoring. ‘We integrate our sensors in steel and make rotating equipment smarter,’ van Genuchten explained.
Other companies are deploying acoustic systems to identify blade delamination, oil analysis for gearbox health, and electrical signature analysis for generator issues. Each technology adds a piece to the puzzle, but the real value comes from integration. The impact of load monitoring alone can be transformative.
As van Genuchten explained, ‘Twenty percent more loading on a gearbox or on a bearing is half of your life. The other way around, twenty percent less loading is double your life.’ With proper monitoring, operators can optimize load distribution across their fleet, extending component life while maximizing production.
But monitoring without action is just expensive data collection. The most successful operators are those who’ve learned to translate sensor data into operational decisions. This requires not just technology but organizational change, breaking down silos between monitoring, maintenance, and management teams.
In Wind Energy Operations, Early intervention makes the million-dollar difference
The economics of early intervention are compelling across every component type. The blade root bushing example from We4Ce illustrates this perfectly. With their solution, early detection means replacing just 24-30 bushings in about 24 hours of drilling work. Wait, and you’re looking at 60+ bushings and 60 hours of work. Early detection doesn’t just prevent catastrophic failure; it makes repairs faster, cheaper, and more reliable.
This principle extends throughout the turbine. Early-stage bearing damage can be addressed through targeted lubrication or minor adjustments. Incipient electrical issues can be resolved with cleaning or connection tightening. Small blade surface cracks can be repaired in a few hours before they propagate into structural damage requiring weeks of work.
Leading operators are implementing tiered response protocols based on monitoring data. Critical issues trigger immediate intervention. Developing problems are scheduled for the next maintenance window. Minor issues are monitored and addressed during routine service. This systematic approach reduces both emergency repairs and unnecessary maintenance, optimizing resource allocation across the fleet.
Turning information into action
While monitoring generates data, platforms like SkySpecs’ Horizon transform that data into operational intelligence. Josh Goryl, SkySpecs’ Chief Revenue Officer, explained their evolution at the recent Customer Forum: ‘I think where we can help our customers is getting all that data into one place.
The game-changer is integration across data types. The company is working to combine performance data with CMS data to provide valuable insights into turbine health. This approach has been informed by operators across the world, who’ve discovered that integrated platforms deliver insights that siloed data can’t.
The platform approach also addresses the reality of shrinking engineering teams managing expanding portfolios. As Goryl noted, many wind engineers are now responsible for solar and battery storage assets as well. One platform managing multiple technologies through a unified interface becomes essential for operational efficiency.
The Integration Imperative for Wind Farm Operations
The most successful operators aren’t just adopting individual technologies; they’re integrating monitoring, inspection, and repair into a seamless operational system. This integration operates at multiple levels.
At the technical level, data from various monitoring systems feeds into unified platforms that provide comprehensive asset visibility. These platforms don’t just display data; they analyze patterns, predict failures, and generate work orders.
At the organizational level, integration means breaking down barriers between departments. This cross-functional collaboration transforms O&M from a cost center into a value driver. Building your improvement roadmap For operators ready to enhance their O&M approach, the path forward involves several key steps:
Assessing the Current State of your Wind Energy Operations
Document your maintenance costs, failure rates, and downtime patterns. Identify which problems consume the most resources and which assets are most critical to your wind farm operations.
Start with targeted pilots Rather than attempting wholesale transformation, begin with focused initiatives targeting your biggest pain points. Whether it’s blade monitoring, gearbox sensors, or repair innovations, starting with your largest issue will help you see the biggest benefit.
• Invest in integration, not just technology: the most sophisticated monitoring system is worthless if its data isn’t acted upon. Ensure your organization has the processes and culture to transform data into decisions – this is the first step to profitability in your wind farm operations.
Build partnerships, not just contracts: look for technology providers and service companies willing to share knowledge, not just deliver services. The goal is building capability, not dependency.
• Measure and iterate: track the impact of each initiative on your key performance indicators. Use lessons learned to refine your approach and guide future investments.
The competitive advantage
The wind industry has reached an inflection point. With increasingly large and complex turbines, monitoring needs to adapt with it. The era of flying blind is over.
In an industry where margins continue to compress and competition intensifies, operational excellence has become a key differentiator. Those who master the integration of monitoring, inspection, and repair will thrive. Those who cling to reactive maintenance face escalating costs and declining competitiveness.
The technology exists. The business case is proven. The early adopters are already reaping the benefits. The question isn’t whether to transform your O&M approach, but how quickly you can adapt to this new reality. In the race to operational excellence, the winners will be those who act decisively to embrace the efficiency revolution reshaping wind operations.
Unless otherwise noted, images here are from We4C Rotorblade Specialist.
Contact us for help understanding your lightning damage, future risks, and how to get more uptime from your equipment.
Download the full article from PES Wind here
Find a practical guide to solving lightning problems and filing better insurance claims here
Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage
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