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Title: Dynamics and control assessment for complex processes : a study of fuel-flexible syngas shifting and gasification
Author: Narvaez-Cueva, Ricardo
ISNI:       0000 0004 8500 849X
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2019
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This thesis presents a model-based controlling proposal for a pilot-scale gasifier with passive syngas shifting components. This control proposal was developed out of a prior dynamic modelling stage and validation of the technological improvements. The first element was the validation of the technology improvement which consisted of an energy-passive, packed-bed structure located in the upper part of the gasifier that removed CO2 from syngas and promoted water-gas shifting. The validation consisted of performing experimental assays with and without the packed-bed structure. Results show that this structure enhanced the cold gas efficiency (CGE) between 24.46% and 40.48%, depending on the inlet air O2 content. The second component was related to the feedstock quality-dependent dynamic modelling of municipal solid waste (MSW) gasification. The modelling approach consisted of a hybrid/ grey box-type model, formed by a transfer function-type structure whose parameters were calculated out of feedstock quality and dynamic operational variables by an ANN-based component. The variables were previously evaluated by feature selection. The results indicated that air flow rate, sulphur content of feedstock, and syngas recirculation flow rate were the most influential attributes. The third component was the development of a self-tuneable proportional, integrative, derivative (PID)-based control loop. The novelty included the dynamic modelling approach of the second component for generating feedstock quality-dependent transfer functions. Results showed that settling time was reduced in up to 21.75% when compared to a regular PID controller. Finally, it was proved that feedstock quality parameters affect the dynamic behaviour of gasification and including this information in model-based PID controllers improves their performance.
Supervisor: Not available Sponsor: SENESCYT (ECU) Scholarship Program
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: Gasification ; Municipal solid waste (MSW) ; Syngas shifting ; System dynamics ; Dynamic modelling ; Artificial neural networks (ANN) ; Model-based PID control