Optimal scheduling of bidirectional energy conversion units in energy and ancillary service markets for system restoration within MCESs
Bibliographic record
Abstract
Multi‐carrier energy systems (MCESs) can be formed by the integration of various energy infrastructures including power and natural gas systems. The proliferation of bidirectional energy conversion units in an MCES can set the stage for a more resilient and robust system. This study shows how bidirectional energy conversion units and storage devices can be optimally scheduled within an MCES for provision of various regulation services to the grid operator. To that end, a new model is proposed for optimal scheduling of power‐to‐gas (PtG), gas‐fired generation, and gas storage units in an MCES. The model aims to facilitate integration of renewables, utilise gas, and power price arbitrage, provide regulation services to the real‐time (RT) market, and contribute to the system restoration. New indices that quantify the contribution of the MCES operator to RT and ancillary service markets are proposed. The proposed model is validated technically and economically by using a test system historical operating data. Numerical results demonstrate that while the proposed model is technically feasible, it also enhances the economic viability of the grid operator.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".