Intelligent event trigger based sliding mode control in a marine current turbine with superconducting magnetic energy storage
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Marine current turbines (MCTs) are a burgeoning renewable energy technology that may effectively capture the kinetic energy of ocean currents to produce power. Nevertheless, the sporadic and uncertain characteristics of marine currents present substantial obstacles to the reliable functioning of grid-connected MCT systems. By incorporating Superconducting Magnetic Energy Storage (SMES) into grid-connected marine current turbines and implementing intelligent event-triggered Sliding Mode Control (ETSMC), we can significantly improve the transient voltage stability of marine renewable energy systems. The sophisticated event trigger mechanism continuously checks the circumstances of the grid and the operation of the turbine in real-time. The real-time nonlinear control technique enhances the performance of SMES by effectively regulating the flow of active and reactive power, hence ensuring grid stability during transient occurrences. This integrated system aims to improve the dependability and effectiveness of marine current turbine operations, thereby supporting the progress of sustainable marine renewable energy technologies. The resilience of the system was evaluated by its implementation in real-time on a dSPACE-DS1104 board, which was connected to an experimental laboratory bench. Additionally, a comprehensive analysis was conducted by comparing actual and simulated data in order to assess both the quantitative and qualitative aspects of the system.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it