A Fully Decentralized Approach for Solving the Economic Dispatch Problem
Why this work is in the frame
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Bibliographic record
Abstract
A new decentralized approach for solving the economic dispatch problem is presented in this paper. The proposed approach consists of either two or three stages. In the first stage, a flooding-based consensus algorithm is proposed in order to achieve consensus among the agents with respect to the units and system data. In the second stage, a suitable algorithm is used for solving the economic dispatch problem in parallel. For cases in which a nondeterministic method is used in the second stage, a third stage is applied to achieve consensus about the final solution of the problem, with a flooding-based consensus algorithm for sharing the information required during this stage. The proposed approach is highly effective for solving the non-convex formulation of the economic dispatch problem and for incorporating transmission losses accurately in a fully decentralized manner. Three case studies that were examined for validation purposes are described. The results obtained demonstrate that the proposed approach aggregates many of the advantages of both centralized and fully decentralized mechanisms for solving the economic dispatch problem.
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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