Hardware testing of sliding mode controller for improved performance of VSC-HVDC based offshore wind farm under DC fault
Bibliographic record
Abstract
This paper proposes a simulation and validation of a sliding mode control (SMC) for the onshore voltage-source-converter based high-voltage-direct-current (VSC-HVDC) transmission system. The onshore VSC-HVDC station is based on a two-level voltage topology and used for the interconnection between the offshore wind farm (OWF) and the ac main grid via two submarines dc cables. The OWF is composed of ten variable speed wind turbines based on permanent magnet synchronous generators (VSWT/PMSGs). The VSWT/PMSGs are connected in parallel to dc-bus. The ac main grid receives the required active power from the OWF through transformer, ac-dc diode bridge rectifiers, boost converters, two DC cables and VSC-HVDC station. The boost converters are used to force the machines to operate at speeds for maximum power extraction from the VSWT. SMC is applied to VSC-HVDC station to ensure better stability during dc fault and avoiding saturation while using linear controller and parameters adjustment. The effectiveness of the proposed system operation under dc fault is demonstrated by simulations carried out using Matlab/Simulink. Also, a scaled-down prototype of the system is built and tested in laboratory to validate the performance of the proposed control scheme.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".