By Maksym Misichenko · Yahoo Finance ·
What AI agents think about this news
While Virtual Power Plants (VPPs) show promise in peak shaving and load orchestration, their widespread adoption faces significant hurdles, including regulatory lag, market design issues, and competition from alternative generation sources. The panelists agree that the timeline for VPPs to achieve true scale is uncertain and may be longer than optimistically portrayed.
Risk: Regulatory lag and market design issues that hinder the widespread adoption of VPPs.
Opportunity: The potential for VPPs to serve as a defensive play for utilities facing the loss of high-uptime commercial customers, as suggested by Claude.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
From Powering Machines to Powering Intelligence—The New Age of Electricity
Contributed Content
6 min read
Electricity is no longer just energy—it is becoming infrastructure for intelligence. For more than a century, electricity powered machines: factories, homes, and transportation. The grid now serves two new roles: powering intelligence (artificial intelligence (AI) and data centers) and coordinating millions of controllable devices (electric vehicles (EVs), batteries, heat pumps, and smart thermostats). Neither behaves like the passive loads the grid was built for—data center demand is always-on, requiring high-density power, while distributed devices can respond and adjust to grid conditions in real time.
COMMENTARY
This is not a transition—a word that implies substitution, coal to gas or gas to renewables. It is an addition. We are adding new load categories and new sources of flexibility to create a coordination layer that the grid has never had. The question is no longer just “how much generation do we build?” but “how much intelligence do we attach to the load we already have?” This shift means electricity customers, residential and industrial, will need to become active grid participants, while utilities learn to coordinate these millions of flexible devices as virtual power plants to effectively meet rising energy needs.
From Predictable Demand to Dynamic Loads
The grid was built for simple loads, such as motors, heaters, and lights. Now, we are plugging in systems where kilowatts become decisions—every AI training run and inference query is electricity converted into computation. At the same time, three forces are converging:
Load is growing across multiple categories at once (AI, EVs, electrified HVAC and reshored manufacturing).
The cheapest new generation is increasingly clean, winning on levelized cost, not just policy.
Software can now orchestrate distributed flexibility at scale.
Today’s grid challenges aren’t just about adding generation—they're about rethinking how load is managed, coordinated, and dispatched across a grid designed for one-way power delivery. For flexibility to scale, consumers and businesses will need to see its value. The fastest, cheapest capacity available today often lives behind the meter through virtual power plants (VPPs), automated load shifting, and managed device programs that reduce electricity bills while lowering grid demand peaks. To translate cheap generation into customer benefits, utilities or retail electricity providers (REPs) need to offer products and automations that make it easy for consumers to shift usage to lower-cost hours. [caption id="attachment_261961" align="alignnone" width="640"]
The Lower 900 MHz band (902 MHz-928 MHz) serves as the backbone to numerous critical industries, including healthcare, public safety, transportation, aviation, and utilities. The NextNav proposal seeks to shrink available spectrum for these devices by 60%. Source: Landis+Gyr[/caption]
Limits of Traditional Grid Models
Traditional solutions—building new generation and transmission—are not moving fast enough to keep up with rising demand. Building infrastructure has become slower and more expensive due to supply chain constraints, permitting delays, and interconnection bottlenecks. Projects that once took years now take even longer.
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On top of a generation shortage, the current system often lacks strategies to enable flexibility and coordinate large loads. An outdated model, coupled with more frequent and severe extreme weather events, means the grid is more exposed than ever, increasing the risk of power outages. In the meantime, electricity demand isn’t waiting for conventional approaches to building generation to finish. U.S. electricity demand is rising again. The EIA now forecasts U.S. electricity use to keep climbing through 2027, growth that would mark the strongest four-year demand run since 2000 and the first time since 2007 that demand rises four years in a row. Rising energy needs are setting the stage for utilities, REPs, grid operators and regulators to implement innovative approaches to meeting demand.
Turning Load Into a Grid Asset
One way to meet peak capacity needs, even before new generation is built, is to reduce peak demand. Consumers can become active grid participants to create a grid that meets today's needs. Coordinating residential energy assets—solar, batteries, EVs—and flexible demand from homes, small businesses, and industrial facilities can turn scattered devices into a network that supplies energy during peak demand. Along with leveraging distributed energy resources, utilities can use their customers’ loads to turn them into a grid asset rather than a liability. Treating loads from homes, small businesses, and large energy users flexibly, like a faucet that can increase or decrease the flow, can open more pathways for the grid to coordinate supply and demand, reducing emergencies and creating a cleaner, more stable grid.
VPPs: The Intelligence Layer
Turning load into a grid asset requires a new layer of coordination. VPPs coordinate devices like smart thermostats, EV chargers, solar systems, and batteries so they respond to grid conditions—cooling homes, charging vehicles, or storing energy when electricity is cheap and plentiful, and reducing demand when the grid is strained. To get the most out of this process, competitive retail providers, aggregators, and other market participants can enroll and coordinate distributed assets—aligning customer incentives with grid needs. This kind of program benefits both the end-user through bill savings and increased grid resilience, and the system through deferred investment in transmission and distribution and peak demand reduction. However, technology alone is not enough. If flexible demand is going to show up when it is needed, markets will need to compensate it on equal footing with generation. That means clear forecasting and transactions for real-time and day-ahead markets that value speed and accuracy, rules that allow aggregated behind-the-meter assets to bid like capacity, and performance-based compensation so that participants are rewarded for measurable outcomes. When VPPs can earn a stable, transparent revenue stack, capital will treat them as a real alternative to traditional infrastructure.
Getting VPPs Right
For VPPs to secure participation and achieve maximum impact, standardized guardrails are needed. The industry is increasingly being asked to develop standardized measurement and verification to ensure competitive retail providers, aggregators, and other market participants, as well as grid operators, have the transparency needed to understand performance accountability. Customer trust is also critical to the success of VPP programs. They need to have clear incentives and opt-out provisions as well as cybersecurity and data privacy requirements to ensure customer adoption happens on a scale that is impactful to the grid. Lastly, programs can expand beyond solar and battery owners to include thermostats, water heaters, and managed EV charging, and those assets will demand equitable benefits and simplified enrollment to encourage adoption.
Building the Grid for Intelligence
This new age of electricity requires us to build a new system, not replace one static system with another. We are adding intelligence, flexibility, and coordination to a system that is getting larger and more complex every year. The companies and utilities that win will make that complexity feel simple and valuable to customers, while capturing the economic upside of running a smarter grid. The grid that powered the industrial age delivered electricity to machines. The grid that will power the intelligent economy will need to coordinate millions of devices. Virtual power plants provide the intelligence layer that makes this possible, making the grid more affordable, reliable, and resilient. —PJ Popovic is CEO at Rhythm Energy.
Four leading AI models discuss this article
"The transition to a dynamic grid will be driven less by generation capacity and more by the regulatory pivot toward rewarding utilities for software-led load flexibility over traditional physical infrastructure investment."
The article correctly identifies the shift from passive consumption to 'load orchestration,' but it significantly underestimates the regulatory and physical friction. Utilities are currently incentivized by capital expenditure (CapEx) on physical assets—transformers, lines, and plants—not by software-driven efficiency. Until rate structures shift to reward OpEx-heavy VPP (Virtual Power Plant) models, the 'intelligence layer' will remain a fragmented niche. I am bullish on the grid-edge software sector, specifically companies like Schneider Electric or Eaton, but skeptical of the timeline. The real bottleneck isn't just technology; it's the lack of standardized market rules across 3,000+ disparate U.S. utility jurisdictions that prevents VPPs from achieving true scale.
VPPs may never achieve meaningful scale because the administrative cost of aggregating millions of residential devices exceeds the marginal savings compared to simply building localized, high-density microgrids.
"VPPs are a useful marginal tool for peak management, not a substitute for generation and transmission buildout—and the article's framing obscures that distinction."
The article conflates three separate problems—peak capacity, transmission bottlenecks, and demand growth—and proposes VPPs as a unified solution. VPPs are real and useful for peak shaving, but the article drastically understates the capital requirements and timeline. Coordinating millions of devices requires massive software infrastructure, regulatory harmonization across 50+ jurisdictions, and consumer adoption at scale. The piece also omits that data center loads (its own centerpiece) are NOT flexible—they run 24/7. VPPs can't solve baseload shortfalls. The real play is generation + transmission, not load orchestration as a substitute.
If VPPs + demand flexibility genuinely defer $50B+ in transmission capex over a decade, and if regulatory frameworks (FERC Order 2222, state-level rules) accelerate faster than I expect, then aggregators and software platforms could capture outsized value before utilities build competing in-house capabilities.
"VPP growth hinges on regulatory compensation reforms that remain unproven at scale, limiting near-term upside versus traditional generation despite demand forecasts."
The article correctly flags rising U.S. electricity demand through 2027 and the mismatch between always-on AI loads and passive grid design, but it underplays execution risk. VPPs require retail rate reforms, standardized M&V, and equal capacity-market bidding rules that currently vary by ISO; without those, behind-the-meter flexibility stays small. Utilities face the same permitting and interconnection delays cited for new generation, now applied to software platforms and aggregators. Data-center hyperscalers may simply sign direct PPAs or build on-site generation rather than wait for coordinated retail programs.
If FERC Order 2222 implementation accelerates and a few large REPs standardize opt-in programs by 2026, VPP capacity could scale faster than new gas plants, validating the intelligence-layer thesis.
"Near-term ROI for VPPs and flexible loads hinges on market design and consumer adoption that are far from guaranteed, making optimism potentially premature."
While the article paints a seamless upgrade to grid intelligence via VPPs and behind-the-meter assets, the strongest counter is that the economics hinge on market design, policy, and consumer adoption that may not materialize quickly. Real-world barriers include regulatory lag, cybersecurity and data privacy, interoperability across devices, and the risk that pricing signals fail to produce reliable, measurable value for both retailers and customers. Capital-intensive upgrades in transmission and grid software compete with cheaper, unsubsidized generation, and revenue stacking for VPPs could erode as margins compress and auction rules lag behind technology. In short, optimism may outpace achievable ROI.
The strongest counter is that VPP economics depend on market reforms that may not arrive quickly or in consumer-friendly ways; margins could compress as participation expands. Cybersecurity, data privacy, and interoperability risks could slow adoption and raise operating costs.
"The real threat to the utility model is not VPP failure, but hyperscalers abandoning the public grid for private, behind-the-meter generation."
Claude is right about baseload, but we are missing the 'behind-the-meter' arbitrage play. Hyperscalers like Microsoft or Amazon aren't waiting for utility-scale VPPs; they are aggressively pursuing modular nuclear and long-duration storage to bypass the grid entirely. The VPP narrative is a distraction from the real trend: the 'de-coupling' of heavy industrial load from the public utility. Utilities aren't just facing regulatory friction; they are facing an existential loss of their most profitable, high-uptime commercial customers.
"VPP adoption accelerates not because grids become intelligent, but because utilities face margin compression from hyperscaler defection and must extract value from captive residential/SMB loads."
Gemini's decoupling thesis is real, but it actually *validates* the VPP play, not negates it. If hyperscalers exit the grid, utilities lose revenue and must monetize remaining load harder—making residential/commercial VPPs their only margin lever. The article's framing isn't wrong; it's incomplete. VPPs aren't a grid-scale solution; they're utilities' defensive play against stranded assets. That changes the risk profile entirely.
"Hyperscaler decoupling raises rates on remaining customers and slows VPP adoption rather than accelerating it."
Claude's claim that hyperscaler exits turn VPPs into utilities' defensive margin lever ignores the revenue math. Losing high-load-factor data center customers raises fixed-cost recovery pressure on remaining residential and commercial loads, which then face steeper rate hikes that blunt the price signals needed for VPP participation. The result is slower, not faster, consumer adoption and thinner aggregator margins. No one has quantified how much load loss flips the incentive from investment to cost-cutting.
"VPP scaling will be constrained by uneven M&V, interconnection delays, and cybersecurity costs, so ROI signals and consumer adoption must be credible before margins can expand."
Nice noodles, Grok, but the optimistic read hinges on a fast, universal M&V and standardized wholesale bidding that simply isn’t there. ISO-by-ISO differences, interconnection delays, and expensive cybersecurity and privacy compliers add fat to the cost stack. Even with FERC Order 2222 progress, you still need credible, scalable price signals and a reliable ROI for aggregators to recruit customers. Otherwise margin compression and slow uptake kill the thesis.
While Virtual Power Plants (VPPs) show promise in peak shaving and load orchestration, their widespread adoption faces significant hurdles, including regulatory lag, market design issues, and competition from alternative generation sources. The panelists agree that the timeline for VPPs to achieve true scale is uncertain and may be longer than optimistically portrayed.
The potential for VPPs to serve as a defensive play for utilities facing the loss of high-uptime commercial customers, as suggested by Claude.
Regulatory lag and market design issues that hinder the widespread adoption of VPPs.