Grid-Forming Voltage-Source Inverter for Hybrid Wind-Solar Systems Interfacing Weak Grids
Bibliographic record
Abstract
This paper presents a grid-forming (GFM) voltage-source inverter (VSI) with direct current regulation for a hybrid wind-solar generator, enabling stable operation at very weak grid conditions and under faults. The GFM-VSI interfaces a hybrid wind-solar generator without an intermediate dc-dc conversion to increase the system efficiency. The wind generator comprises a wind turbine with a permanent magnet synchronous generator (PMSG) interfaced by a voltage-source rectifier (VSR). The PMSG-VSR and a solar photovoltaic (PV) array are connected to the GFM-VSI's dc-side. The VSR is responsible for extracting wind power with a power reserve option. The GFM-VSI is implemented to extract solar power with a power reserve capability and support the grid voltage or reactive power. The stable operation of the proposed system is validated under very weak grid conditions, and it is shown that a similar hybrid wind-solar system with grid-following control is unstable under the same weak grid conditions. A complete small-signal state-space model of the proposed hybrid system is developed and analyzed. Nonlinear time-domain simulations and real-time simulation tests verify the model's accuracy and show the proposed system's effective performance under challenging operating scenarios, such as grid uncertainties and faults.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".