Transient Thermodynamic Assessment of the World's First Grid Connected UWCAES Facility by Exergy Analysis
Bibliographic record
Abstract
Experience with Toronto's Underwater Compressed Air Energy Storage (UWCAES) facility has shown the technology to be more versatile than originally anticipated. Beyond typical steady-state operations, potentially valuable ancillary grid service roles can be assumed in the transient phase of its operation. This study examines the challenge to operate efficiently during UWCAES ramping events. A conventional and advanced exergy analysis is here conducted for the world's first grid connected UWCAES facility located in Toronto, Canada. A conventional exergy analysis showed that under real working conditions, the exergy efficiency of the plant is low during start-up. The exergy destruction rate, under unavoidable conditions, 2 minutes after the start of the transient phase is 42%, and this decreases asymptotically to 25%. An advanced analysis of exergy efficiency through a complete charge/discharge cycle suggested that the first improvement priority be given to the Heat Exchangers group. This should then be followed by the Ancillary, Compressor, Turbine, Motors and Generator and Pipelines groups. In terms of the rate of exergy destruction the analysis indicated that improvement priority for the Compressor group was higher than that for Heat Exchangers followed by Ancillary, Motors and Generator, Turbine and Pipelines groups. The advanced exergy analysis also revealed that 67% of the exergy destruction was endogenous and avoidable, highlighting the significant potential for performance improvement. Moreover, it was shown that with improvement in the system's component efficiencies, the plant exergy efficiency could be exogenously improved. This effect could further reduce the total exergy destruction to 76%, where only 9% is due to component-component interaction.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".