Energy and Economic Assessment of Oxy-Fuel Combustion CO2 Capture in Coal-Fired Power Plants
Bibliographic record
Abstract
Oxy-fuel combustion technology replaces air with a mixture of pure O2 and recycled flue gas for coal combustion, which leads to difficulties in the waste heat recovery of flue gas in the boiler tail of coal-fired power plants. This paper proposes a new integration scheme for waste heat recovery of flue gas in coal-fired power plants with oxy-fuel combustion CO2 capture. By introducing an oxygen preheater, a recycled flue gas preheater, and a low-pressure economizer, the waste heat of flue gas is fully recovered to preheat oxygen, recycled flue gas, and feed water, respectively. The proposed scheme simultaneously ensures the safe operation of the recycled fan and improves the thermal performance of the coal-fired power plants. Compared to the air combustion configuration, the boiler’s efficiency and gross power efficiency in the oxy-fuel combustion configuration are increased by 0.42% and 1.29%, respectively. Due to power consumption for the added equipment, the net power efficiency is reduced by 10.41%. A techno-economic analysis shows that the cost of electricity for oxy-fuel combustion in coal-fired power plants has increased from USD 46.45/MWh to USD 80.18/MWh, and the cost of the CO2 avoided reaches USD 43.24/t CO2.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".