Performance Assessment of a Multi-Rotor Floating Tidal Energy System
Bibliographic record
Abstract
Performance assessments of full-scale tidal turbines have been carried out for multiple machines deployed globally and reported in literature. The rotor number and diameter of the demonstrated tidal energy converters differs from single rotor devices in the MW class to scalable arrays of comparably small turbines. For multi-rotor systems (MRS), potential interaction, positive or negative, remains a key research question. Previous studies at Sustainable Marine prototype system (PLAT-I 4.63) have implied that variations in the incoming flow field are highly likely to cause deviations in rotor performance. Sustainable Marine has developed and built the pre-commercial PLAT-I 6.40 platform. PLAT-I 6.40 has been connected to the Canadian grid in May 2022. Between May and end of September 2022 the system has been undergone comprehensive commissioning and performance trials. PLAT-I 6.40, carries six 4m diameter SCHOTTEL Instream Turbines (SIT), each rated at 70 kW. This work presents the results of full-scale field tests that focussed on the assessment of differences in the performance between the individual turbines during summer 2022. To evaluate the variances in the flow field across all rotors, a specific test campaign has been conducted, where a flow speed sensor was sequentially positioned upstream of each turbine while a second flow measurement device was stationary as reference. For all test configurations the power curves have been determined following the guidance of the IEC TS 62600-200 based on the flow speeds measured with both devices. This paper presents the experimentally obtained power curves for each test configuration and compares it against the reference values. The results show that there are steady differences in the flow field resulting in varying power outputs across the different rotors (Figure 1). However, a comparison of the individual rotor power curves with the design predictions shows good agreement.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".