Resilient interconnected microgrids (IMGs) with energy storage as integrated with local distribution networks for railway infrastructures
Bibliographic record
Abstract
This paper is aiming to development and design of Interconnected Microgrids (IMGs) with effective strategies for integrated energy storage and hybrid Distributed Energy Resources (DERs) with the distribution lines so that it can store energy in the off peak for re-use during the day. One potential application is the integration with the railway infrastructures as a new green technology. This goal will be achieved by proposing heuristic technique to enable interconnected MGs to work transparently with the recent energy storage. Railway transportation MG model is proposed to balance energy flows between trains moving and braking energy, energy storage system and a main power utility network. The paper proposes an energy optimization tool for the interconnected railway-MG system. Artificial Bee Colony Algorithm (ABC) is applied for achieving the economical cost during the operation. Digital simulation scenario has been validated by real data; the achieved results show the impact and effectiveness of the proposed strategies.
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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".