The power sector is experiencing a fundamental shift. AI-driven data center buildouts, electrification mandates and grid reliability concerns are driving demand for new generation capacity at a pace the industry hasn’t seen in decades. And for investors, developers and operators trying to allocate capital across that landscape, the question is no longer just which assets to pursue—it’s how you actually compare them.
A combined cycle gas plant in Texas. A utility-scale solar farm in New Mexico. A four-hour battery storage project in California. Each carries a different risk profile, a different revenue structure and a fundamentally different operational logic. Yet capital allocation decisions require putting all three on the same scale. That’s the challenge and it’s one that the power investment world hasn’t solved cleanly.
The Problem: Power Asset Classes Were Never Built to Be Compared
Three Asset Types at a Glance
| Natural Gas | Solar PV | Battery Storage | |
|---|---|---|---|
| Revenue Driver | Energy & capacity markets; spark spread | PPA off-take; capacity factor | Energy arbitrage; ancillary services; capacity payments |
| Dispatch Type | Often misjudges arrival and duration of cold snaps or warm-ups | Intermittent (daylight hours only) | Flexible (charges & discharges on price signal) |
| Capex Profile | Higher upfront; stable over time | Declining rapidly ($/MW) | Tied to battery duration ($/MWh) |
| Key Risk Factor | Fuel price & carbon policy exposure | Curtailment risk; PPA counterparty quality | Revenue stack volatility; market rule changes |
| Underwriting Complexity | Moderate – heat rate, utilization assumptions | Moderate – irradiance, degradation curve | High – duration, stacked revenue sources |
Source: Enverus Power & Renewables | For illustrative purposes
Natural gas, solar and storage differ in almost every financial dimension that matters to an investor.
Natural gas earns revenue through energy and capacity markets, with dispatch economics tied to fuel costs, heat rates and spark spreads. Its returns are sensitive to gas prices, carbon policy and utilization assumptions. A gas plant that looks excellent at $3.50/MMBtu looks materially different at $5.00. Capex is typically higher upfront, but the asset can generate revenue around the clock — making it a baseload or peaking play depending on configuration.
Solar PV operates on a completely different financial structure. Revenue is a function of irradiance, capacity factors and contracted off-take — typically a power purchase agreement (PPA) at a fixed or indexed price. Capex has fallen dramatically and continues to decline, but solar is intermittent by nature. It generates during daylight hours, which creates both curtailment risk and basis risk depending on how congested the local market gets around noon. Evaluating a solar deal requires understanding the shape of generation, the quality of the PPA counterparty and the long-run degradation curve of the panels.
Battery storage is the most structurally complex of the three. It doesn’t generate power — it arbitrages it. Revenue comes from a combination of energy arbitrage, ancillary services (frequency regulation, spinning reserves) and increasingly, capacity payments. Duration matters enormously: a two-hour battery and a six-hour battery are nearly different asset classes from an investment standpoint. And the revenue stack is more volatile and less contracted than a typical PPA, meaning underwriting storage requires a fundamentally different set of assumptions about market structure.
The result: comparing a gas plant to a solar farm to a battery project using a single spreadsheet model means rebuilding your assumptions from scratch every time or worse, forcing incompatible assets into the same template and hoping the outputs are meaningful.
Most investment teams do something in between. They run separate models. They apply different discount rates subjectively. They benchmark against other deals they’ve seen rather than operating data. And they take weeks to get to a first-pass view on any single opportunity.
What Happens When You’re Evaluating at Scale
The problem compounds quickly when you’re not evaluating one asset and you’re evaluating a pipeline of them.
Consider a fund or developer that’s actively screening 50 opportunities across gas, solar, wind and storage in each quarter. Each asset type requires its own modeling conventions. Each team member has built their model slightly differently. PPA pricing assumptions vary. Capex benchmarks are pulled from memory or stale comps. The result is a portfolio of financial models that are internally consistent but externally incomparable. You can’t rank a solar project against a gas plant against a storage deal in any reliable way because the underlying assumptions were
never standardized.
This is a structural problem with how power assets have historically been underwritten: one deal at a time, by specialists in each technology, using bespoke models. That approach made sense when gas dominated new capacity additions and the competitive set was narrow. It doesn’t work in a market where all three technology types are competing for the same capital simultaneously.
“You can’t rank a solar project against a gas plant against a storage deal in any reliable way when the underlying assumptions were never standardized.”
The teams that are winning in this environment are building systems, a standardized financial framework that lets them evaluate gas, solar and storage on a consistent basis, rank them against real operating benchmarks and stress-test economics quickly across scenarios.
What “Apples to Apples” Actually Requires
A true cross-asset comparison framework for power investment needs to do several things consistently:
- Standardized financial outputs.
IRR, NPV, and payback period needs to be calculated using the same methodology across all asset types — same treatment of depreciation, tax equity, debt structure and
terminal value.
- Consistent capex benchmarking.
Actual installed costs per MW – not developer proformas. Reflecting what gas, solar and storage really cost to build today, by region.
- Technology-appropriate revenue modeling.
Gas runs on spark spread. Solar runs on PPA structure. Storage runs on a stacked revenue model. Each handled correctly — without rebuilding the logic.
- Real-world operating benchmarks.
Returns benchmarked against how similar projects actually performed, not what was promised at financial close.
- Scenario flexibility.
Power prices are up 20%. Capex over budget by 15%. Any framework that requires rebuilding from scratch to answer those questions is too slow.
The Stakes Are High — And Getting Higher
~62 GW
new power capacity needed by 2030
to meet AI data center demand
~42%
rise in PPA prices across
key U.S. markets since 2022
~16%
year-over-year growth in
U.S. battery storage capacity
under construction (1Q25-1Q26)
The urgency here isn’t abstract. The AI-driven surge in power demand is repricing generation assets across all technology types simultaneously. Data center developers are signing long-term offtake agreements at prices that would have seemed unrealistic three years ago. Transmission constraints are creating regional basis differentials that significantly affect asset economics. The Inflation Reduction Act continues to reshape the economics of solar, wind and storage through the tax credit landscape.
In this environment, investment decisions made on the basis of stale benchmarks, inconsistent models, or incomplete scenario analysis carry real downside risk. A gas plant underwritten against 2021 capex numbers may no longer pencil the way the original model suggested. A storage project benchmarked only against developer projections, without reference to how comparable projects have actually performed, may carry execution risk that isn’t showing up
in the IRR.
The teams that are moving fastest and with the most conviction are the ones who’ve solved the apples-to-apples problem and who can screen hundreds of assets across all three technology types in days rather than weeks, benchmark against real operating performance and stress-test key assumptions without rebuilding from scratch.
The Solution: Power Plant Portfolio Economics
That’s exactly the problem Enverus built Power Plant Portfolio Economics to solve.
Power Plant Portfolio Economics delivers standardized, investment-grade financial analytics — IRR, NPV, payback period — across thousands of generation and storage assets, calculated using consistent methodology regardless of technology type. Gas, solar, wind and battery storage are all evaluated on the same financial framework, so your team can compare a combined-cycle plant in the Gulf Coast against a solar-plus-storage project in the desert Southwest without rebuilding a single model.
The platform draws on actual operating and completed project data, not developer projections so your benchmarks reflect how assets actually perform in real market conditions. And scenario testing is built in: adjust capex, PPA pricing, or operating cost assumptions on the fly to run upside, downside and base-case views instantly.
For investment teams operating at scale, funds screening large pipelines, developers prioritizing where to allocate development capital, operators benchmarking their portfolio against the market — it’s the difference between evaluating ten deals a month and evaluating a hundred.
The power sector is moving faster than it ever has. The investment teams that will win are the ones who can see the whole picture, compare assets on equal footing and move from screening to decision in minutes, not weeks.
Want to see how Power Plant Portfolio Economics works across your asset pipeline? Request a demo at Enverus.com
