MétaCan
Menu
Retour à la cohorte
Enregistrement W7128726211 · doi:10.26180/4679455

Towards flexible operation of post-combustion CO₂ capture from brown coal derived flue gas

2017· dissertation· W7128726211 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueMonash University · 2017
Typedissertation
Langue
DomaineEngineering
ThématiqueCarbon Dioxide Capture Technologies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFlue gasProcess (computing)Power stationSoftware deploymentRange (aeronautics)Pilot plantElectricityCoal

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,128
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,010
Tête enseignante GPT0,205
Écart entre enseignants0,195 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle