Performance Evaluation of Evaporative Compressor Inlet Air Cooling System in a Gas Turbine-Based Cogeneration Plant
Bibliographic record
Abstract
Gas turbine-based power plants are very sensitive to ambient conditions and their output power and efficiency can be decreased significantly with increase in the ambient temperature. Various compressor inlet air cooling systems have been proposed and utilized to reduce inlet air temperature to the system, including evaporative systems e.g. media and fogging, and mechanical cooling systems. In this work, different techniques for compressor inlet air cooling are briefly reviewed. Then, the fogging system employed in the Whitby cogeneration power plant is explained with particular attention to the location of the system installation. A model of the gas turbine-based cogeneration plant is also developed to simulate the Whitby cogeneration power plant. The effects of fogging compressor inlet air cooling system on the performance of the plant are investigated. The results indicate that at an ambient temperature of 30°C and relative humidity of 40% the inlet cooling of as high as 8.4°C is possible which can increase output power to more than 50 MW. Also, it is found that the model can predict the gas turbine exhaust temperature and the plant’s power production with the error level of lower than 0.5% and 3%, respectively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".