A decentralised electricity market model: An electric vehicle charging example
Bibliographic record
Abstract
Decentralized competitive markets are essential for a meaningful growth of distributed generation. Currently most jurisdictions use administered prices at the retail level. Through the example of electricity trade at an electric vehicle charging facility, this paper presents a trade mechanism that can help create decentralized markets. The mechanism is based on random matching and subsequent bargaining between the electricity sources and the electric vehicles. The entity organizing the market sets designated trade parameters. The ensuing interaction between the electricity sources and the vehicles, where each is trying to maximise its own benefit, is modeled as a non-cooperative game of incomplete information. Equilibrium analysis and examples are used to demonstrate the merits of this mechanism. In comparison to the market clearing price based approaches, this model provides market governance capabilities that can help tune a market to local requirements. The distribution companies may find the model useful as it will allow gradual introduction of localised markets and thereby enable phasing in of the investments required for upgrade of distribution infrastructure to service the electric vehicle charging needs.
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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".