A Preliminary Assessment of the Competitiveness of Wave Energy Technologies: A Regionally Detailed Analysis
Bibliographic record
Abstract
In this paper, a regionally disaggregated global energy system model treating the electricity supply sector in detail is used to examine the competitiveness of wave energy technologies for each of 48 world regions over the period to 2050 under a constraint of halving global energy-related CO2 emissions in 2050 compared to the 2000 level. It is first found that wave energy continues to be uncompetitive until 2050 due to (1) its high cost and (2) the large seasonal variability of wave power. Even if the reference wave electricity generation costs are assumed to be reduced by 90%, the latter factor severely limits the market penetration of wave energy technologies. It is then found that the UK and Ireland, Australia and New Zealand, Japan, South Africa, the western US, Latin America, Canada, and Spain and Portugal are the regions promising for wave energy deployment. Not only low-cost and abundant wave energy resources, but also the peak electric load in winter, the relatively small seasonal variability of wave power, and/or the low competitiveness of power sources substitutable by wave energy are the reasons for this.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".