Generation maintenance scheduling in virtual power plants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In an active network, as a virtual power plant (VPP), periodic maintenance of distributed generators (DGs) is critically vital for the reliable operation of the power system. To prevent unexpected failure of DGs and avoid deterioration of the grid's reliability, coordination of maintenance scheduling is indispensable. In this study, maintenance management of a VPP is proposed for scheduling the planned outage of DGs, in order to preserve their useful lifespan. In addition to conventional DGs and the upstream power grid, renewable generation including wind turbines and photovoltaic systems, energy storage systems, and curtailable loads are considered as components of the VPP. The proposed maintenance scheduling scheme provides different advantages in viewpoints of cost and reliability. Moreover, risk management is also investigated to lower the risk of maintenance scheduling due to the uncertainty in price in an energy market by adopting the conditional value at risk as a measure of risk. The overall cost is minimised considering the power loss in the grid as well as the security constraints such as DGs operational constraints, voltage magnitude, and transmission lines’ power flow limit. The effectiveness of the proposed scheme is illustrated using numerical studies with short‐ and long‐term scheduling.
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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) | 0.000 | 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