On the Instability Mechanism of PV-Thermal-Bundled Power System Under Different PV Penetration Ratios
Bibliographic record
Abstract
In the photovoltaic (PV)-thermal-bundled power system, the increasing PV penetration poses instability risk. Through establishing the small-signal model and solving the eigenvalues of return ratio matrix, the system stability can be evaluated with the generalized Nyquist stability criterion. However, the expressions of eigenvalues are irrational functions, which leads to the complexity of analyzing the system stability and the difficulties to accurately reveal the instability mechanism. To address this issue, the stability analysis method based on the admittance matrix elements is proposed, which does not need to calculate the eigenvalues of return ratio matrix, thus simplifying the stability analysis. In addition, this method can describe the system stability margin clearly. With this stability analysis method, the stability of the PV-thermal-bundled power system is clarified under different renewable penetration ratios, and the causes of the system instability are investigated. Finally, the hardware-in-the-loop results confirm the effectiveness of the proposed stability analysis method and the accuracy of the stability analysis results.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".