Distributed sustainable generation dispatch via evolutionary games
Bibliographic record
Abstract
Today's power grid is provisioned conservatively for rarely occurring demand peaks. These peaks are served by flexible generation systems that are typically costly and have significant carbon footprint. Distributed power sources such as wind turbines and solar panels are sustainable but unreliable as these have inherently variable generation capacities. An effective power dispatch management system is necessary to harness the significant generation potential of these intermittent systems. In this work, a novel scheme is proposed which leverages upon the recent cyber-enablement in the power grid to distributively dispatch a large number of strategically interacting small-scale variable generators. We incorporate evolutionary game theoretic techniques into the formulation of the dispatch strategy as it provides an opportunity to model the aggregate behaviour of tactical agents making inter-dependent decisions and aids with establishing deterministic steady state predictions of the system state. Numerical and theoretical results presented in this work show that the proposed strategy is highly scalable and enables real-time power dispatch of intermittent systems while maintaining low computational overhead.
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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 | 0.000 |
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 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".