A Multi-Stage Strategy for Harnessing Congestion Management Services from Industrial Hubs in Local and System-level Markets
Bibliographic record
Abstract
This paper introduces a multi-stage coordination model incorporating industrial hubs, distribution system operators (DSOs), and the transmission system operator (TSO) into separate stages within a hierarchical optimization framework. In this concept, the hubs incorporate electrical, thermal, and cooling storage systems, enabling them to participate in integrated demand response (IDR) programs. This model effectively harnesses the flexible capacities of industrial hubs in congestion management (CM) markets, integrating dispatchable units and battery storage systems under their management, thereby facilitating the transfer of flexibility from distribution-level to transmission-level markets. The proposed model is implemented using GAMS on the IEEE 14-bus transmission network, connected to two IEEE 21-bus distribution networks at buses 5 and 9. Simulation results demonstrate that the proposed decentralized scheme significantly reduces CM costs at both the TSO and DSO levels, while also increasing the daily profits of the hubs from CM markets.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".