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The influence of different parameters on biomass gasification in circulating fluidized bed gasifiers
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-0895-8286
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-5341-3656
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-1351-9245
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-6279-4446
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2016 (English)In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 126, p. 110-123Article in journal (Refereed) Published
Abstract [en]

The mechanism of biomass gasification has been studied for decades. However, for circulating fluidized bed (CFB) gasifiers, the impacts of different parameters on the gas quality and gasifiers performance have still not been fully investigated. In this paper, different CFB gasifiers have been analyzed by multivariate analysis statistical tools to identify the hidden interrelation between operating parameters and product gas quality, the most influencing input parameters and the optimum points for operation. The results show that equivalence ratio (ER), bed material, temperature, particle size and carbon content of the biomass are the input parameters influencing the output of the gasifier the most. Investigating among the input parameters with opposite impact on product gas quality, cases with optimal gas quality can result in high tar yield and low carbon conversion while low tar yield and high carbon conversion can result in product gas with low quality. However using Olivine as the bed material and setting ER value around 0.3, steam to biomass ratio to 0.7 and using biomass with 3 mm particle size and 9 wt% moisture content can result in optimal product gas with low tar yield.

Place, publisher, year, edition, pages
2016. Vol. 126, p. 110-123
National Category
Chemical Process Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-32432DOI: 10.1016/j.enconman.2016.07.031ISI: 000385326400011Scopus ID: 2-s2.0-84980563382OAI: oai:DiVA.org:mdh-32432DiVA, id: diva2:951015
Available from: 2016-08-04 Created: 2016-08-04 Last updated: 2018-02-26Bibliographically approved
In thesis
1. Biomass gasification in fluidized bed gasifiers: Modeling and simulation
Open this publication in new window or tab >>Biomass gasification in fluidized bed gasifiers: Modeling and simulation
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Using woody biomass as a resource for production of biofuel, heat and power through gasification has been studied for years. In order to reduce the cost of operating and to design the full-scale gasification plant developing a general model to be applicable for different ranges of input data with acceptable level of accuracy, is needed. In order to develop such model for the gasifier, as the main component in the process, three major models have been studied in this thesis; theoretical model (Equilibrium model), semi-empirical model (modified equilibrium model, kinetic combined with hydrodynamic model) and empirical model (statistical model).

Equilibrium model (EM), shows low accuracy in predicting the content ofmajor components in product gas especially CH4 and CO. Therefore to improve the accuracy of prediction modification of EM is needed. Analyzing the semi-empirical approaches show that although the accuracy of EM can be improved, the generality of the modified models are still low. Therefore two new modified models have been developed. The first model is based on including data from wider range of operating condition to develop the empirical equation. The second model is based on combining QET and reaction kinetics for char gasification approaches. The first model decreases the overall error from 44% to 31% while the overall error of second model is decreased from 36% to 8%. Other semi-empirical model for fluidized bed gasifiers which is not equilibrium-based is developed by combining reaction kinetics with hydrodynamic equations. Investigating different hydrodynamic models show that combining two-phase-structure model with reaction kinetics for bubbling fluidized bed gasifiers improves the accuracy of the kinetic-only model.

The third type of approaches, investigated in this thesis, towards developing a general model is the empirical model. This model has been developed based on Partial least square (PLS) approach. The PLS-R model show high level of accuracy within the specific range of empirical data used for developing the model. Further analysis on the experimental dataset by PLS-R model show that equivalence ratio (ER) is the operating parameter with the most significant impact on the performance of fluidized bed gasifiers. Optimizing the operation of fluidized bed gasifiers based on this model shows that high gas quality (high volume fraction of H2, CO and CH4 and low volume fraction of CO2), high carbon conversion and low tar yield is achieved when ER≈0.3, Steam to Biomass ratio≈0.7, moisture content≈9% and particle size≈3mm and olivine is the bed material. 

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2016
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 216
National Category
Chemical Process Engineering Energy Systems
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-33426 (URN)978-91-7485-296-7 (ISBN)
Public defence
2016-12-02, Pi, Mälardalens högskola, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2016-10-18 Created: 2016-10-18 Last updated: 2016-11-11Bibliographically approved
2. Near-Infrared Spectroscopy and Extractive Probe Sampling for Biomass and Combustion Characterization
Open this publication in new window or tab >>Near-Infrared Spectroscopy and Extractive Probe Sampling for Biomass and Combustion Characterization
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Biomass is characterized by highly variable properties. It can be converted to more valuable energy forms and products through a variety of conversion processes. This thesis focuses on addressing several important issues related to combustion and pulping.

Experimental investigations were carried out on a biomass-fired industrial fluidized-bed boiler. The observed combustion asymmetry was explained by an imbalance in the fuel feed. Increased levels of carbon monoxide were detected close to boiler walls which contribute significantly to the risk of wall corrosion.

Moreover, extensive literature analysis showed that near-infrared spectroscopy (NIRS) has a great potential to provide property information for heterogeneous feedstocks or products, and to directly monitor processes producing/processing biofuels in real-time. The developed NIRS-based models were able to predict characteristics such as heating value, ash content and glass content. A study focusing on the influence of different spectra acquisition parameters on lignin quantification was carried out. Spectral data acquired on moving woodchips were found to increase the representativeness of the spectral measurements leading to improvements in model performance.

The present thesis demonstrates the potential of developing NIRS-based soft-sensors for characterization of biomass properties. The on-line installation of such sensors in an industrial setting can enable feed-forward process control, diagnostics and optimization.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2017
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 224
National Category
Energy Systems Chemical Process Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-35041 (URN)978-91-7485-317-9 (ISBN)
Public defence
2017-04-26, Pi, Mälardalens högskola, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2017-03-20 Created: 2017-03-19 Last updated: 2017-04-18Bibliographically approved

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Mirmoshtaghi, GuilnazSkvaril, JanCampana, Pietro EliaLi, HailongThorin, EvaDahlquist, Erik

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