Eco-Technoeconomic Analyses of Natural Gas-Powered SOFC/GT Hybrid Plants Accounting for Long-Term Degradation Effects Via Pseudo-Steady-State Model Simulations
Bibliographic record
Abstract
Abstract In this study, four solid oxide fuel cell (SOFC) power plants, with natural gas (NG) as the fuel source, that account for long-term degradation were designed and simulated. The four candidate SOFC plants included a standalone SOFC plant, a standalone SOFC plant with a steam bottoming cycle, an SOFC/ (gas turbine) GT hybrid plant, and an SOFC/GT hybrid plant with a steam bottoming cycle. To capture dynamic behaviors caused by long-term SOFC degradation, this study employed a pseudo-stead-state approach that integrated real-time dynamic 1D SOFC models (degradation calculation embedded) with steady-state balance-of-plant models. Model simulations and eco-techno-economic analyses were performed over a 30-year plant lifetime using matlab simulink R2017a, aspen plus V12.1, and python 3.7.4. The results revealed that, while the standalone SOFC plant with a steam bottoming cycle provided the highest overall plant efficiency (65.0% LHV), it also had high SOFC replacement costs due to fast degradation. Instead, the SOFC/GT hybrid plant with a steam bottoming cycle was determined to be the best option, as it had the lowest levelized cost of electricity ($US 35.1/MWh) and the lowest cost of CO2 avoided (−$US100/ton CO2e).
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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) | 0.000 | 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".