Towards flexible operation of post-combustion CO₂ capture from brown coal derived flue gas
Bibliographic record
Abstract
The world’s first commercial-scale CO₂ capture plant in Boundary Dam power station uses amine-based post-combustion CO₂ capture (PCC) technology (Boundary Dam, Canada). The issues of large energy requirement and high cost have hindered worldwide deployment of PCC. Flexible operation has been proposed as a way to improve the economic and technical feasibility of PCC. Flexible operation coordinates reductions in CO₂ emissions with electricity demand by: (i) ramping up CO₂ capture during periods of low energy demand, and (ii) turning down or switching off CO₂ capture during high energy demand. The immediate and long term impact of process disturbances from flexible operation is unclear. This thesis investigates the technical influence of flexible operation during amine-based CO₂ capture from brown coal derived flue gas. Dynamic pilot plant studies have provided practical experience in flexible operation of PCC plants. The pilot plant study demonstrates the successful implementation of flexible operation in the form of parameter step-changes to a PCC process. The PCC pilot plant is run by CSIRO and located at AGL Loy Yang in Australia. The operation of the PCC plant under a broad range of transient conditions has captured the dynamics of the process and provides suitable data dynamic model validation. Additionally, the density meters provide the advantage for online monitoring of liquid CO₂ concentration. Statistical analysis revealed that data variance may occur due to changes in: (i) ambient temperature, (ii) MEA concentration, or (iii) amine degradation. Although PCC plants of different scales and configurations have different response times, it is likely the dynamic trends to parameter changes would be similar. Thus, the dynamic behaviour observed in this thesis is of greater significance compared to the absolute values. Based on this study, changing the flue gas flow rate would produce the most rapid response. The greatest CO₂ removal percentage was achieved at the lowest flue gas flow rate or at the highest absorbent flow rate. However, the latter provides high CO₂ removal percentage with significantly lower reboiler heat duty in terms of MJ/kg CO₂. The steam pressure parameter provides the ability to adjust the temperature of all the columns simultaneously. This effect may be used to compensate for effects from ambient conditions or heat losses. Flexible operation of PCC is modelled using Aspen Plus Dynamics®. Dynamic modelling of flexible PCC operation in the pilot plant uses the following stand-alone models: (i) Absorber Column 2 (ABS2), (ii) Absorber column 1 (ABS1), and (iii) Stripper Column. Stand-alone models provide the advantage of greater flexibility compared to integrated models; also they carry-through of successive errors is avoided. Additionally, disturbances can be introduced to intermediate streams without convergence issues. Each stand-alone model simulates the following flexible operation scenarios: (i) step-changes in flue gas flow rate, (ii) step-changes in absorbent flow rate, and (iii) step-changes in steam pressure. Modelling of property changes individually, elucidates which properties generate the dynamic responses observed in the pilot plant. The overall effect observed in the step-changes scenarios was the result of a combination of property changes that occur in tandem. The combination of these property changes accurately describes the dynamic behaviour observed in the pilot plant results. Although the dynamic modelling could not replicate the absolute values obtained in the pilot plant, the models demonstrated the same trends observed in pilot plant results. The modelled behaviour and pilot plant observations are in agreement for comparisons of the following results: (i) column temperature, (ii) CO₂ composition of the liquid product, (iii) CO₂ composition of the vapour product, and (iv) CO₂ removal/capture percentage. Modelled dynamic response is in agreement with pilot plant trends, despite the influence of non-ideal conditions (e.g. amine degradation, ambient temperature effects, heat loss). Some key novel outcomes of the dynamic modelling include: (i) Model specifications in Aspen Plus® and Aspen Plus Dynamics® are based on data from the CSIRO PCC pilot plant at AGL Loy Yang; (ii) Modelling of a PCC process with a double-absorber configuration; (iii) The process of converting equilibrium reactions into forward/reverse kinetic reactions is documented in detail; (iv) The number of equilibrium stages for this PCC study is greater compared to previous Aspen Plus Dynamics® studies by Lin et al. (2011), Lin et al. (2012) and Léonard et al. (2013); (v) Demonstrated the necessity of adjustment factors to achieve model agreement with experimental data (particular when pilot plant data is affected by non-ideal conditions); (vi) Compared the precision of different mass transfer coefficient correlations for rate-based PCC modelling.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".