Assessment of the IEEE 1547-2018 Frequency-Droop Function for PV Inverter Operation
Bibliographic record
Abstract
As modern grids shift towards renewable energy (RE), new challenges arise with higher penetration of inverter-based distributed energy resources (DER). The variability and intermittency of RE also pose significant challenges for grid operation. Therefore, DER standards are updated/revised with new grid support functions to ensure proper grid operation with higher penetration of renewable energy. This paper presents an assessment of the frequency-droop function from the recently revised IEEE 1547-2018 standard. The function is assessed using high-resolution solar photovoltaic (PV) system production data from commercial PV inverters of a 5 MW solar farm. Several issues with the current droop function implementation is discussed. In addition, PV energy curtailment with different settings of the droop function is also assessed. The results are presented using the datasets of five days with different levels of solar variability. The daily energy curtailment can be as high as 4.1% and 13.2% with IEEE 1547 and CSA C22.3 No. 9 standards respectively.
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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 | 0.000 | 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) | 0.001 | 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 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".