A Control for Preventing False Tripping of Grid-Tied Renewable Systems With Increased Solar Penetration and Fluctuating Load Demand
Bibliographic record
Abstract
High penetration of solar energy systems leads to power variability at point of common coupling (PCC). This accompanied with high demand fluctuations, reflects as highly fluctuating effective loading at PCC. This leads to fictitious jump in estimated frequency by phase/frequency locked loops (PLLs/FLLs) due to associated voltage phase angle jumps at PCC during such power variability. This fictitious frequency jump translates into triggering synchronization control leading to false tripping of power electronic switch isolating system from grid. This is more dominant in highly variable renewable dominated sources such as solar power generating systems (SPGS). This work presents a control to prevent occurrence of fictitious jumps in estimated frequency by incorporating an approach to decouple amplitude and phase/frequency estimation loops, and providing additional immunity to frequency loop against any phase transients. Additionally, a blinder arrangement is proposed to minimize trip attempts to ensure steady state phase/amplitude matching during synchronization. Proposed methodology improves system operation and reliability. It also improves power quality performance during supply voltage and load current distortions. Simulation and experimental results are provided to validate performance with presented methodology.
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.
How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".