Virtual Power Plants Face a Scale-and-Evidence Test

Sunjoo Hwang and Noah Kittner published their 2025 Progress in Energy review as volume 7, article 022008, titled “Virtual power plants: bridging utility and customer gaps to facilitate clean energy transitions.” It evaluates U.S. virtual power plants through existing programs and a California case study. The accompanying interview supplies no program sample sizes, measured savings, emissions changes or funding disclosure, so the available material presents the principal benefits as proposals rather than verified outcomes.

A virtual power plant aggregates batteries, rooftop solar, electric vehicles, smart thermostats and flexible loads, then coordinates them through software. The model seeks to bridge the utility-customer gap by delivering grid services traditionally supplied by large centralized plants, including peak management, balancing and emergency support.

What operational problem do virtual power plants address?\n

The U.S. case combines extreme-weather exposure, conventional plant retirements and expected load growth from electrification, electric vehicles, artificial intelligence and data centers. Variable renewable generation adds another balancing requirement, while new centralized infrastructure and fossil-fuel peaker operation can raise costs, emissions and air pollution.

The review anticipates that coordinated resources could reduce peak demand, supply backup during grid emergencies and absorb more renewable power. It also links potential public-health and environmental gains to lower peaker reliance, noting that peakers are disproportionately located near disadvantaged communities.

What evidence supports the savings claims?

The review reportedly surveys existing U.S. programs and uses California to examine real-world performance, cost and emissions. A single California case study cannot establish a national result, and the interview reports no enrolled megawatts, dispatch hours, response times, baselines, savings, reliability metrics or emissions totals.

For an R&D or utility portfolio decision, those omissions prevent calculation of implementation cost, avoided generation cost and return on investment. The supplied material gives no implementation budget either, so managers cannot compare programs on either capital requirement or operating performance.

Where does scale break down?\n

The review identifies customer participation, compensation, affordability, equity and business models as barriers. It argues that utilities, customers and communities need aligned incentives before virtual power plants can scale. For budget planners, unresolved compensation and participation rates matter because a dispatchable resource has little operating value if enrolled assets cannot respond or remain available.

Kittner said: “The challenge is not simply developing these technologies, but creating systems that can integrate them efficiently while maintaining reliability and affordability.” His proposed integration layer includes advanced demand response, vehicle-to-grid systems and intelligent controls.

Which technologies could change the economics?\n

Long-duration storage, advanced power electronics and flexible electricity systems could support grids with very high renewable shares across hours, days and seasons. Kittner prioritizes storage that is inexpensive, durable, safe and based on abundant materials because those attributes shape lifecycle cost, procurement exposure and the feasibility of sustained dispatch.

Artificial intelligence and advanced modeling could identify cost-effective decarbonization pathways, optimize energy systems in real time and improve assessment of climate and extreme-event risks. These remain proposed applications, not demonstrated results in the supplied material; no model accuracy, response time or planning outcome appears.

Can equity become part of the investment case?\n

The review extends beyond U.S. deployment. Kittner points to emerging economies with fast-growing energy needs and constraints in capital, infrastructure and technical expertise, and calls for financing, technology transfer and international collaboration.

That agenda addresses whether clean systems can be affordable and resilient rather than merely technically available. The supplied material gives no project financing terms, country allocations or technology-transfer timetable, so the pathway remains a development priority without an implementation benchmark.

What are the authors’ credentials?

Kittner studies regional and international grids, community-owned microgrids and household energy dynamics. Current projects include energy-system planning in Thailand, Laos and Myanmar, coal-plant emissions and health effects in Kosovo, and battery assessment for electric-vehicle and stationary-storage applications.

He holds a PhD in Energy and Resources from UC Berkeley, where he studied energy systems engineering, science and policy. His work with the Renewable and Appropriate Energy Lab has appeared in Nature Energy, Environmental Science & Technology and Ecological Economics.

Kittner also served as a Fulbright Fellow at Bangkok’s Joint Graduate School of Energy and the Environment and worked on the Thai Solar PV Roadmap with Chulalongkorn University. He earned a BS in Environmental Science, with highest honors and dual minors in mathematics and urban planning, from the University of North Carolina at Chapel Hill. The accompanying material names no funding source or conflict statement for the review.

What would make scale credible?

Kittner said: “Ultimately, the breakthrough I most want is a combination of technologies and institutions that makes a clean, reliable, affordable, and equitable energy system the easiest choice—not simply the ideal one.” The next decision cycle should require enrolled capacity, baselines, dispatch performance, cost, emissions and benefit allocation from each pilot.

If those measures show repeatable savings and reliability gains, virtual power plants could become a lower-cost alternative to fossil peakers and new central infrastructure. Without them, the concept still has technical merit, but the available evidence does not support a deployment forecast.