Integrating Turbine Blade Cooling With Exhaust Gas Recirculation for Enhanced Carbon Capture in Combined Cycle Gas Turbine
Bibliographic record
Abstract
Abstract In this article, we present the investigation toward the feasibility of turbine blade cooling using exhaust gas from the exhaust gas recirculation (EGR) in combined cycle gas turbine (CCGT) power plants for enhanced carbon capture (CC). The study has been performed due to the need to develop more economical solutions for carbon capture in current CCGTs during the transition toward net zero. Commercially mature CCGTs are the most efficient technology for power generation through fossil fuels and are widely used due to their higher flexibility, reliability, and lower emissions compared to other power generation technologies. Postcombustion CC offers a solution to reduce CO2 emissions from CCGTs. However, the low CO2 concentration in exhaust gas results in a high CC energy demand, leading to high operating costs (OPEX), and the large volumetric exhaust flowrate requires large CC equipment and, thus, high capital costs (CAPEX). Based on theoretical studies, it is generally accepted that EGR should be applied in the current CCGTs to reduce exhaust flow and increase its exhaust CO2 concentration. However, as EGR reduces oxygen concentration at the combustor inlet, the allowable recirculation of exhaust gas is limited by the minimum oxygen content required in the combustor to avoid flame instability and carbon monoxide emission. In this study, we explore an innovative approach that uses exhaust gas for cooling the turbine blade, referred to as exhaust gas cooling (EGC), as a potential solution for further increasing the CO2 concentration in the exhaust and reducing exhaust mass flow without impact on combustion, leading to smaller CC units and lower CC energy consumption in existing utility-scale CCGTs, which are currently cooled using compressor bleed air. An H-class Mitsubishi M701JAC power plant with three pressure level reheat bottoming cycle is modeled in wtemp (Web-Based Thermo-Economic Modular Program) software, a modular cycle analysis tool developed at the University of Genova. Carbon capture from the exhaust gas is performed using a monoethanolamine (MEA) CC unit, modeled in aspen plus v14. A fraction of recirculated exhaust gas, compressed by an auxiliary EGC compressor, is used for cooling the turbine blades and the remaining is mixed with inlet air before gas turbine intake. Simulations were performed while maintaining an oxygen concentration of 16% (by mol.) at the combustor inlet. The impact of EGR-based turbine cooling on CCGT full load performance is evaluated in terms of efficiency and CC plant penalty. Results showed that, compared to conventional EGR, for the same O2 fraction at the combustor inlet, replacing compressor bleed air with exhaust gas for turbine cooling can increase the EGR ratio from 0.35 to 0.40 and reduce the exhaust mass flow by 91.2 kg/s (14.4%) in an H-class CCGT, leading to an increase in CO2 exhaust concentration by 15.32%. As a result, the size of the CC columns and their heat consumption were slightly reduced. With EGC, the power plant efficiency also increased by around 2% mainly due to the use of exhaust gas with high specific heat for cooling. Therefore, the study demonstrates a novel concept that can be implemented in current CCGT power plants for enhanced carbon capture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".