Estimating Frequency Changes Due to Smart Grid Functions
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Bibliographic record
Abstract
This paper presents a new approach for estimating the frequency changes (Df) due to the application of smart grid functions. The proposed approach is based on constructing a ZIP model to represent the power demands at certain point-of-supply, which feeds loads subject to smart grid functions. The constructed ZIP model provides a relationship between the active and reactive power demands and the frequency at that point-of-supply. Such a relationship can be formulated as a set of nonlinear equations that can be numerically solved for Df. The load-model based approach is implemented for performance evaluation using the IEEE 30 bus power system. Performance results show that the proposed approach has a simple implementation, and can provide an accurate estimation of frequency changes over long time intervals. Furthermore, the load-model approach is found capable of maintaining its accuracy without being affected by load demands, power ratings, and/or duration of demand changes.
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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) | 0.002 | 0.001 |
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 it