A dual time-scale optimal dispatch algorithm for PV systems: Integrating centralized optimal power dispatch with distributed power deviation absorption in DC smart grids
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Bibliographic record
Abstract
The integration of Photovoltaic (PV) systems into DC smart grids faces challenges due to solar power’s inherent unpredictability. Traditional dispatch methods struggle to effectively manage PV power deviations in real-time. This paper proposes a dual time-scale strategy integrating centralized optimization with distributed consensus. On the long-term scale, a convex relaxation-based optimal power flow model minimizes line losses and stabilizes voltages. For short-term adjustments, a distributed consensus algorithm dynamically allocates power deviations among PV sources using reserve capacity, eliminating the need for probabilistic uncertainty modeling. The approach is validated through IEEE 14-node simulations and hardware-in-loop (HIL) tests, with comparisons against centralized methods considering forecast errors. The results demonstrate enhanced voltage stability, highlighting the framework’s practicality for real-time grid management.
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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 | 0.001 |
| 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 it