Nuclear Power Stocks Screener Excel: Track AI Data Center Energy Demand Plays (May 2026)

Nuclear power stocks screener Excel - if you landed on this page, you are most likely trying to put structure around the most confusing trade in the May 2026 market: how to size the basket of nuclear-exposed equities that AI data center demand has suddenly made interesting again. The universe runs from regulated mega-cap utilities to pre-revenue small modular reactor developers, the headlines move on PPA announcements rather than earnings prints, and the data you need is scattered across 10-Ks, NRC dockets, and press releases. This guide ships a working Excel workbook that pulls all of that into one screener, scores each name on AI-PPA exposure, and lets you compare four very different sub-sectors on a single tab.

This is not a generic "best nuclear stocks to buy" listicle. It is a screener template, a methodology, and a structured way to keep score as the nuclear renaissance unfolds week by week.

Why a Nuclear Power Stocks Screener Excel Now

Through most of the last decade, nuclear was a sleepy corner of the utility sector. Coal-to-gas had been the substitution story, renewables were taking incremental megawatts, and aging US reactors were being retired without replacement. Then three things happened almost at once.

First, hyperscaler power demand exploded. The training and inference workloads of frontier AI models pulled forward years of data center build-out, and operators discovered that no other generation source could match nuclear on the three metrics that matter for an AI campus: 24/7 dispatchability, near-zero carbon footprint, and the ability to deliver a gigawatt behind a single fence line.

Second, the public-market story repriced. Constellation Energy, Vistra, and Talen Energy all signed long-duration power purchase agreements with hyperscalers in 2024 and 2025. The PPAs locked in premium prices for decades and shifted the cash-flow profile of merchant nuclear generation from cyclical to contracted.

Third, the SMR (small modular reactor) cohort moved from concept to commercial reality. Oklo, NuScale, and a wave of pre-revenue developers attracted capital on the thesis that the next gigawatt of dispatchable carbon-free generation will be modular and behind-the-meter.

The result is that as of May 2026 we have four very different sub-sectors all wearing the same "nuclear" label:

A real screener has to acknowledge that those four buckets do not behave the same way. A regulated utility that owns one nuclear plant trades like a bond proxy. A pure-play uranium miner trades like a leveraged bet on the spot. An SMR developer trades like venture-stage equity. Bucketing them into one "nuclear" ETF blurs the trade you are actually trying to express.

This template does the bucketing for you.

What the Nuclear Power Stocks Screener Excel Ships With

The workbook has six tabs designed to flow from "what is the universe" to "how do I score each name" to "how do the sub-sectors compare to each other."

1. How To Use - tutorial, sheet guide, scoring methodology, risk notes, and an educational-use disclaimer. Required reading on first open.
2. Main Dashboard - the screener. Yellow input cells for portfolio size, sub-sector allocation cap, minimum composite score, and four score-weight inputs. The body of the sheet is a 17-row table with live price, market cap, 52-week distance, P/E, dividend yield, beta, RSI, earnings growth, and the composite AI Score.
3. AI Data Center Scoring - the engine. Each ticker gets scored on four dimensions: nuclear percentage of generation, signed-PPA flag, contracted PPA revenue percentage, and a sub-sector multiplier. The weights live on the Main Dashboard so you can re-weight the model without touching this sheet.
4. Capacity & Fuel - nameplate nuclear MW, total MW, nuclear share of capacity, last price, market cap, 1-year analyst target price, and implied upside.
5. Quality + Fundamentals - P/E, dividend yield, ROE, debt-to-equity, revenue growth, EPS growth, payout ratio, and Altman Z score. A PASS / REVIEW quality flag is computed off ROE and debt levels.
6. Sub-Sector Heatmap - the four buckets aggregated to median market cap, P/E, dividend yield, ROE, debt-to-equity, and EPS growth. This is the tab you screenshot when you brief a client.

Every sheet ends with a "MarketXLS Functions Used in This Sheet" reference block so a user always knows which function is powering which cell.

The sample workbook ships with illustrative static values plus the formula reference next to each cell. The template workbook ships with live MarketXLS formulas only and refreshes on every Ctrl+Alt+F9. Both files use the same six-sheet structure.

The Composite AI Data Center Score Explained

The composite score on the Main Dashboard is the most opinionated part of the workbook, so it gets the most explanation.

AI Score = (Nuclear % of Generation x W1) + (Signed PPA Bonus x W2)
         + (PPA % of Revenue x W3) + (Sub-Sector Multiplier x W4)

The default weights are 30 / 30 / 25 / 15 and they sit in editable yellow cells on the Main Dashboard. Every other sheet references those cells, so if you decide PPA exposure should weigh more than nuclear share you change one cell and the screener re-ranks instantly.

• Nuclear % of Generation rewards the operator-owners (CEG ranks highest at over 65% nuclear, NRG ranks at zero).
• Signed PPA Bonus is a binary 100 / 0 toggle that fires when a company has publicly disclosed a hyperscaler PPA.
• PPA % of Revenue scales the bonus by how material the contract actually is. A 5% revenue contribution looks different from a 35% revenue contribution.
• Sub-Sector Multiplier is a base score per bucket. SMR developers carry the highest multiplier because the entire equity is exposed to the AI thesis. Engineering carries the lowest because the revenue is diversified across many end markets.

The higher the AI Score, the larger the exposure to the AI-data-center-power thesis. Higher is not better. Higher just means more concentrated. A conservative dividend buyer might deliberately tilt toward the lower scores. A thematic basket builder might tilt toward the top quartile.

The screener is a tool for being explicit about that choice.

The Sub-Sector Map (Why Bucketing Matters)

This is the table the template surfaces on the Sub-Sector Heatmap sheet, with median values across each bucket. Numbers are illustrative.

The story told here is the one a screener is supposed to tell.

Utility operators look like classic dividend payers. P/E in the low twenties, yield around 2%, modest growth, balance sheets leveraged in the way utilities always have been. Cash flow is regulated, so the volatility is low. This is where a retired allocator parks nuclear exposure.

Merchant generators look like a different animal entirely. Same notional sector but the EPS growth median jumps to 26% because the PPA pricing is repricing the cash flow base. Beta is higher, dividend yield is lower, and the upside (if PPA contracts execute) is mathematically much larger than a regulated utility can offer. This is where the AI-thesis bid is most concentrated.

Uranium miners look like a commodity sleeve. Trailing P/E ratios are sky-high because trough-year earnings still anchor the multiple, but EPS growth is positive and accelerating as long-term contracts re-price. The trade is on the spot uranium price, not on US power demand directly.

SMR / Fuel / EPC is the most heterogeneous bucket. BWXT and FLR have real revenue and real margins. OKLO and NuScale are pre-revenue. The median P/E is meaningless because most names do not have one. The right way to look at this sub-sector is as a venture-stage basket gated on regulatory milestones.

A nuclear power stocks screener Excel template is useful precisely because it forces you to look at the buckets separately rather than averaging them into a single score that hides what is going on.

Building Each Cell in MarketXLS

The template ships with formulas, but you can rebuild every column from scratch with the MarketXLS add-in. Every formula below has been verified against the MarketXLS function library and is live as of May 2026.

For the price and market context columns on the Main Dashboard:

=QM_Last("CEG")                       Real-time price for Constellation Energy
=MarketCapitalization("VST")/1E9      Market cap in billions of dollars
=FiftyTwoWeekHigh("CCJ")              52-week high price
=(QM_Last("CEG")/FiftyTwoWeekHigh("CEG"))-1   Distance from 52-week high
=Beta("DUK")                          Beta versus S&P 500
=RSI("OKLO")                          Relative Strength Index (14-period default)

For the fundamentals columns on Quality + Fundamentals:

=PERatio("CEG")                       Trailing P/E ratio
=DividendYield("DUK")                 Trailing 12-month dividend yield
=ReturnOnEquity("VST")                Trailing return on equity
=TotalDebtToEquity("PEG")             Total debt divided by shareholder equity
=QuarterlyRevenueGrowthYOY("TLN")     YoY quarterly revenue growth
=QuarterlyEarningsGrowthYOY("CEG")    YoY quarterly EPS growth
=PayoutRatio("XEL")                   Dividend payout ratio
=AltmanZScore("CCJ")                  Altman Z-score

For the analyst-consensus and target-price block on Capacity & Fuel:

=OneYrTargetPrice("CEG")              Consensus 12-month analyst target
=(OneYrTargetPrice("CEG")/QM_Last("CEG"))-1   Implied upside vs spot
=Sector("OKLO")                       GICS sector
=Industry("BWXT")                     GICS industry

For the sub-sector medians on the Sub-Sector Heatmap:

=MEDIAN(MarketCapitalization("CEG")/1E9, MarketCapitalization("PEG")/1E9, MarketCapitalization("DUK")/1E9)
=MEDIAN(IFERROR(PERatio("CEG"),""), IFERROR(PERatio("DUK"),""))
=MEDIAN(DividendYield("CEG"), DividendYield("DUK"), DividendYield("SO"))

Every formula is wrapped in IFERROR in the template so the SMR and pre-revenue tickers (OKLO, SMR, UEC, DNN) do not blow up the sheet when they hit a function that has no value to return.

If you want to extend the universe, drop new tickers into column A of the Main Dashboard and copy the formulas down. The composite score sheet keys off the ticker column, so adding a name flows through all six tabs.

The Inputs That Matter

The yellow cells on the Main Dashboard control everything downstream:

• Portfolio Size: dollar value to be allocated across the basket. Position sizing on the Strategy sheet uses this.
• Max Sub-Sector Allocation: cap on any single bucket. Defaults to 35% so no single sub-sector can dominate.
• Min Composite Score: filter for the screener. Names below this score get highlighted for review.
• Score Weights: four cells, one per dimension. Must sum to 1.00. The model will run with any weights you input, but skewed weights will skew the ranking.

These four inputs are the only knobs you turn. Everything else flows from them.

The point is to make your assumptions explicit. If you believe SMR optionality matters more than near-term contracted PPA revenue, raise the Sub-Sector Multiplier weight and lower the PPA Revenue weight. The screener will re-rank and the heatmap will re-color. You should never be guessing what assumption is driving a ranking.

How to Use the Nuclear Power Stocks Screener Excel Each Week

The workbook is designed for a 15-minute weekly review, not a daily trade. The cadence:

1. Open the template, refresh data with Ctrl+Alt+F9. Every cell that depends on price, P/E, ROE, target price, RSI, or dividend yield updates.
2. Scan the Main Dashboard. Look for tickers where the composite AI Score has changed materially week over week. Score changes usually mean either price moved (changing the implied upside) or a new PPA was disclosed (you updated the PPA columns on the AI Scoring tab).
3. Read the Sub-Sector Heatmap. If one bucket is now showing extreme median valuation versus another, that is the screener telling you the relative trade has moved.
4. Update PPA columns when news drops. This is the one manual chore. When a new hyperscaler PPA is announced, change the "Signed PPA?" cell to "Yes" and update the PPA Rev % cell. The composite score updates instantly.
5. Re-check Quality Flags. Names that drop from PASS to REVIEW deserve a second look. Usually it means leverage ticked up or ROE compressed.

Fifteen minutes a week, and you have a structured view across 17 names and four sub-sectors. That is the value the template ships.

What the Screener Does Not Do

A screener is not an oracle. Three things the template explicitly does not do:

• Predict PPA wins. The PPA columns are manual data points you maintain. The template does not scrape press releases or read SEC filings. If a new contract is signed and you have not updated the cells, the model is stale.
• Cover non-US nuclear. The universe in the workbook is US-listed. Companies like Kazatomprom, EDF, or Korea Hydro are not in the screener. Add them in column A if you want them.
• Generate trade recommendations. The composite AI Score is an exposure metric, not a buy signal. A high score means "leveraged to the thesis," not "go long here." Always pair the screener with your own fundamental analysis.

The screener is a structured way to keep track of a universe. Combined with primary research and a written investment process, that is useful. Used alone, it is just a spreadsheet.

Internal MarketXLS References

If you want to go deeper on the building blocks, these MarketXLS pages cover the foundations:

• MarketXLS home - the add-in landing page.
• Book a Demo - schedule a walkthrough with the team.
• AI CapEx Tracker Excel - Hyperscaler Q1 2026 - the companion template that tracks the data center build-out feeding the power demand.
• Utilities Earnings Tracker Excel - Q1 2026 Power Demand Watchlist - sector view that gave rise to the nuclear cut.
• Energy Earnings Tracker Excel Q1 2026 - context on the broader energy complex.

Download the Nuclear Power Stocks Screener Excel

Download the templates:

• - pre-filled with illustrative May 2026 values plus the live MarketXLS formula name next to each cell.
• - live MarketXLS formulas, zero hardcoded data, refresh with Ctrl+Alt+F9.

Both files use the same six-sheet structure and the same composite AI Score methodology. Pick the static version to see the methodology end-to-end. Pick the live version when you have the MarketXLS add-in installed and want the data to refresh.

FAQ

What is a nuclear power stocks screener Excel and how does it work?

A nuclear power stocks screener Excel is a workbook that takes a defined universe of publicly traded nuclear-exposed equities, pulls quantitative metrics on each name, scores them on a composite that emphasizes the metrics you care about, and lets you compare sub-sectors side by side. The template in this guide pulls 17 tickers, scores them on AI data center PPA exposure, and aggregates the results into a sub-sector heatmap.

Which stocks are included in the nuclear power stocks screener Excel?

The default universe covers four sub-sectors: utility operators (CEG, PEG, DUK, SO, D, XEL), merchant generators (VST, TLN, NRG), uranium miners (CCJ, UEC, DNN), and SMR / fuel / EPC (OKLO, SMR, BWXT, LEU, FLR). You can extend the list by adding tickers in column A of the Main Dashboard.

How do I know if a stock has a hyperscaler PPA contract?

The Signed PPA flag and PPA Revenue % cells on the AI Data Center Scoring sheet are manual data points. You update them when a new contract is announced. Sources include company press releases, 10-K and 10-Q disclosures, hyperscaler sustainability reports, and industry trade publications. The template does not auto-scrape PPA news.

Can the nuclear power stocks screener Excel handle SMR pre-revenue companies?

Yes. The formulas are wrapped in IFERROR so that pre-revenue tickers like OKLO and SMR return blanks rather than errors for P/E, ROE, and payout ratio. The composite AI Score still works because it does not require those cells to be populated. The Quality Flag will return REVIEW for those names because they do not meet the ROE / debt rules, which is the intended behavior.

Do I need the MarketXLS add-in to use this template?

The static sample workbook works in any version of Excel without the add-in. The live formula version requires MarketXLS to be installed and authenticated. The MarketXLS function library powers every price, ratio, and growth figure in the template version. See marketxls.com for the add-in and marketxls.com/book-demo for a walkthrough.

Is this nuclear power stocks screener Excel investment advice?

No. The composite AI Score and Quality Flag are exposure and screening metrics, not buy or sell signals. The template is an educational tool for organizing a thesis and tracking a universe of stocks. Always combine the screener with primary research, your own investment process, and consultation with a licensed financial advisor.

The Bottom Line

A nuclear power stocks screener Excel template is the right tool for the May 2026 nuclear setup because the trade is genuinely confusing. The universe spans regulated utilities, merchant generators, uranium miners, and pre-revenue SMR developers, all wearing the same sector label. Each bucket trades on a different driver. The headlines move on PPA announcements rather than quarterly earnings. The composite AI Score in this workbook lets you express a view on which dimension you think matters most, the sub-sector heatmap lets you compare the buckets cleanly, and the live MarketXLS formulas keep the fundamentals fresh without manual data entry.

Use the template as a 15-minute weekly check-in, update the PPA columns when news drops, and let the screener re-rank the universe each time the data refreshes. Pair it with primary research and a written investment process, and you have a structured way to keep score on one of the more interesting setups in the equity market right now.

Get the MarketXLS add-in at marketxls.com or book a walkthrough at marketxls.com/book-demo to see the live version in action.