First author
Research question
Can existing and new U.S. nuclear power plants improve their economics and operating flexibility by adding high-temperature electrolysis, hydrogen storage and batteries, and by selling energy, hydrogen and ancillary services?
Key insight
With the assumed hydrogen credit, hydrogen revenue can sustain an existing reactor but not pay for a new one
The study treats an existing reactor's capital as already spent, so revenue from power, hydrogen and reserves, with the assumed hydrogen credit, must cover running costs and the new equipment; most reactors studied then reached positive net present value. A new plant must also recover the reactor's capital cost, and new builds stayed below zero even with tax credits.
Why does hydrogen help an existing reactor more than a new one?
A reactor earns from electricity; with an electrolyzer it can also sell hydrogen and offer reserves, and a hydrogen production credit adds to that. The study treats an existing reactor's capital as already spent, so these revenues need to cover operating costs and the new equipment. A new plant must also recover the reactor's capital cost, and in the study the same revenues did not cover it.
Illustrative model with stylized numbers: it shows the mechanism described in the paper, not the study's data or results.
My contribution
First author. I did most of the work: the methodology, the optimization and lifetime techno-economic models (developed during my internship at Idaho National Laboratory), the analysis and the writing.
How I approached it
ChallengeSeven U.S. markets price energy and ancillary services differently, and each of 42 reactors faces its own prices.
What I didI co-developed an hourly dispatch model that co-optimizes electricity sales, hydrogen production, storage and ancillary services under each market's products, run for every reactor.
Why it matteredIt showed how market design, not only the reactor, shapes the value of flexibility.
ChallengeElectrolyzers and turbines are not ideal: efficiency varies with load, starts wear equipment, and ramping is limited.
What I didI helped represent turbine and electrolyzer efficiency with piecewise-linear curves, track electrolyzer degradation from operation and start-ups, and enforce ramp limits and minimum stable load.
Why it matteredFlexibility estimates then respect what the equipment can actually do.
ChallengeOne year of hourly dispatch had to become a lifetime investment case under several federal credits.
What I didI co-developed a discounted cash-flow model with component-level capital costs, scheduled replacements and the 45U, 45V-type, 45Y and 48E credits, linked to the dispatch results.
Why it matteredThe same operation could be judged as a retrofit (with and without 45U) or as a new build (no credit, 45Y or 48E); the hydrogen credit is assumed throughout.
Design choices
- Take electricity and hydrogen prices as given (price-taking)
- Alternatives considered: equilibrium or game-theoretic market models with price feedbackThe study evaluates plant operation against observed 2024 prices; price feedback from wide adoption is stated as a limit and left to future work.
Method
Hourly mixed-integer optimization of turbine, electrolyzer and storage dispatch for 42 reactors in seven U.S. ISO/RTO markets using 2024 prices, linked to a lifetime cash-flow model with federal tax credits (45U, a 45V-type hydrogen credit, 45Y and 48E).
Key findings
- Operated as baseload-only plants at 2024 market prices, nearly all reactors studied had negative net present value.
- With hydrogen integration, including the assumed hydrogen production credit, a majority of the reactors reached positive net present value.
- Integrated operation added output flexibility; ancillary-service revenue was a few percent of the total.
- For new builds, investment and production tax credits substantially lowered the levelized cost of hydrogen.
Boundary conditions
Results rely on 2024 prices, price-taking market participation, modeled ancillary-service participation parameters, the assumed hydrogen credit ($3/kg for ten years) and a dispatch held fixed after the credit expires; price feedback from large-scale adoption is not modeled.
What it led to
New plants did not pay for themselves here, which raised the question of what could cover a new reactor's capital cost; AI data centers are the candidate buyer my next studies examine. Small modular reactor cogeneration for a hyperscale data center
Publications
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Nat. Commun.Rethinking the economics and flexibility of U.S. nuclear power through hydrogen integration and policy supportNature Communications, vol. 17, article 7090, 2026.
@article{Li2026, author = {Li, Honglin and Huang, Jianqiao and Poudel, Bikash and Sun, Mucun and Westover, Tyler and Wendt, Daniel and Zhang, Jie}, title = {Rethinking the economics and flexibility of {U.S.} nuclear power through hydrogen integration and policy support}, journal = {Nature Communications}, volume = {17}, pages = {7090}, year = {2026}, issn = {2041-1723}, doi = {10.1038/s41467-026-73630-y} }
Citation counts: Google Scholar, October 30, 2026.
Outputs
Reproducibility
Model framework with documentation, examples and tests on GitHub. Since v1.1.0 it also includes the article's 2024 PJM price inputs (hourly energy and ancillary-service prices) with their source, provenance and PJM's terms of use; the other examples run on synthetic data.
Last updated 2026-11