Estimated economic load dispatch based on real operation logbook
Bibliographic record
Abstract
The economic load dispatch (ELD) problem of electric power systems has been solved by many techniques including traditional and modern optimization algorithms. The main problem of achieving this task is that all precise specifications of the generating units are required. Also, in practice, many power systems are operated without considering the ELD strategy due to the lack of experience to deal with this part, which is embedded as a package in the energy management system (EMS), and/or the difficulty of constructing precise constrained objective functions matched with the real generating units. Based on a fact that most power systems maintain their daily records, the estimated economic load dispatch (EELD) can be determined using these recorded datasheets. This novel method can be applied without using any special software, and it is an optimization free technique. Moreover, this technique does not require to determine any parameter nor constraint on the generating units, and all candidate solutions are practical and feasible. The proposed method is tested with a real power system data and it shows encouraging results.
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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) | 0.000 | 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 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".