Market-based mechanisms for smart grid management: Necessity, applications and opportunities
Bibliographic record
Abstract
The support of two-way flow of information and electricity in smart grid enables the effective use of market-based mechanisms which promises to ensure fair and efficient resource allocation and, at the same time, provide economical and reliable electricity services to power consumers. In this next-generation power grid, a variety of energy management challenges such as balancing the demand and supply, improving energy efficiency, and maximizing the utility of consumers can be tackled by market-based mechanisms. This paper presents the necessity of applying market-based mechanisms to smart grid management by analyzing the essential characteristics of both market-based mechanisms and smart grid; reviews the application of market-based mechanisms to three typical smart grid management domains, namely smart home energy management, microgrid load balancing and electric vehicle charging. We also discuss challenges and important research opportunities in applying market-based mechanisms to smart grid management, which, we believe, is a high-potential research area.
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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".