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Offshore Floating Solar Photovoltaics for Land Constrained and Diverse Supply Conditions in the United States and Canada

2025· article· en· W4413822860 on OpenAlexaboutno aff
Gabriel Lopez, Dmitrii Bogdanov, Rasul Satymov, Christian Breyer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicOil, Gas, and Environmental Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaicsSubmarine pipelineEnvironmental sciencePhotovoltaic systemEngineeringOceanographyGeologyElectrical engineering

Abstract

fetched live from OpenAlex

Energy transition pathways for large continental areas are largely understood to be achievable using a diverse set of onshore renewable energy technologies. Previous research for the integrated United States and Canada energy-industry system indicated that solar photovoltaics (PV) may dominate the primary energy structure, complemented by onshore wind power. However, societal constraints may require increased supply diversity, and onshore renewable energy may not be sufficient for densely populated regions, especially on the east coast of the United States. The LUT Energy System Transition Model was applied to investigate the role of offshore floating solar PV coupled with offshore wind and wave power when onshore solar PV is limited. The results indicate that, when onshore solar PV is limited to 60% of electricity generation, 434 GW of offshore floating PV may be installed as part of a hybrid power plant sharing the same grid connection as offshore wind power, which reaches 414 GW of installed capacity, contributing 3.1% and 8.1% to the electricity supply, respectively. In total, 7.2 TW of solar PV capacity are installed, complemented by 1.7 TW of onshore wind power. Increased supply diversity still leads to a 42% reduction in levelized cost of electricity, reaching 33.1 euro/MWh in 2050. Compared to cost-optimal conditions, the levelized cost of final energy and non-energy use in 2050 increases by 14% to 47.0 euro/MWh. Nevertheless, such increased costs may be justifiable to meet societal constraints, and a diverse Power-to-X Economy structure for the United States and Canada may still be techno-economically viable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.222
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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