Simulation of hybrid biomass gasification using Aspen plus: A comparative performance analysis for food, municipal solid and poultry waste

Ramzan, Naveed; Ashraf, Asma; Naveed, Shahid; Malik, Abdullah

doi:10.1016/j.biombioe.2011.06.005

Cited by 276 publications

(120 citation statements)

References 17 publications

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“…Actualmente, se ha reportado su aplicación en diferentes sistemas de reacción y separación, así como a plantas de procesos completos, encontrándose buena concordancia entre datos reales y datos determinados a través de las simulaciones en el software [4][5][6][7]9,11,13]. El software también permite definir subrutinas específicas en lenguaje FORTRAN o construir migración de datos a Excel que amplía el panorama de posibilidades en la elaboración de simulaciones específicas.…”

Section: Descripción Del Modelounclassified

“…Encontraron que ambos reactores presentan resultados similares para la obtención de syngas a una presión 2,5MPa y que la tecnología de lecho arrastrado puede considerarse como alternativa para la gasificación a pequeña escala. Ramzan et al [6] desarrollaron un modelo en equilibrio para la gasificación de biomasa mediante el software Aspen Plus. Realizaron análisis de sensibilidad para evaluar el efecto de la temperatura, la relación equivalente, el contenido de humedad de la biomasa y la relación vapor-biomasa en el poder calorífico del syngas, la producción de H 2 y la eficiencia en frío (CGE).…”

Section: Introductionunclassified

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Gasificación de madera para la obtención de un syngas útil en la producción de biocombustibles y/o productos químicos

Hernández

Bayer

Zapata

2017

rev.ion

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ResumenEn el presente trabajo se desarrolló un modelo en equilibrio que permite simular el proceso de producción de un syngas útil para la obtención de biocombustibles líquidos y/o productos químicos mediante gasificación en lecho arrastrado. El proceso fue modelado mediante el software Aspen Plus, considerando las etapas de pretratamiento y acondicionamiento de la biomasa (secado, torrefacción y molienda), gasificación en lecho arrastrado, limpieza y acondicionamiento del syngas producido, y ajuste de la relación H 2 /CO, adicionalmente se modela la Unidad de Separación de Aire (ASU) para la producción de oxígeno como agente gasificante. La validación del modelo se realizó a partir de datos experimentales reportados en la literatura, mediante el análisis de los errores relativos para las variables de interés: relación H 2 /CO, poder calorífico inferior (LHV, de sus siglas en inglés Lower Heating Value) y eficiencia en frío, obteniendo errores de 7,8%, 11,8% y 8,8%, respectivamente. Adicionalmente, se evaluó la sensibilidad del modelo para predecir el efecto de variables de proceso como la temperatura de torrefacción y la relación equivalente sobre las variables respuesta H 2 /CO y LHV, obteniendo con el modelo tendencias similares a las reportadas en la literatura bajo diferentes condiciones de operación, lo cual muestra que el modelo es sensible a cambios en los parámetros del proceso. Por tanto, se considera que el modelo desarrollado es una herramienta computacional útil para realizar análisis de sensibilidad en procesos de producción de biocombustibles líquidos y/o productos químicos a partir de gasificación de biomasa en lecho arrastrado. Palabras clave: gasificación en lecho arrastrado, Aspen Plus, biocombustibles líquidos, biomasa, syngas.Abstract A model to simulate the entrained flow gasification process to produce a syngas useful in the synthesis of liquid biofuels and/or chemicals was developed. The model is simulated in Aspen Plus and includes the stages of: pretreatment and conditioning of biomass (drying, torrefaction and grinding), entrained flow gasification, cleaning and conditioning of syngas produced, adjustment of H 2 /CO relation, and an Air Separation Unit (ASU) for oxygen production as gasifying agent. The model validation was performed from experimental data reported in the literature, by analyzing the relative errors for the interest variables: H 2 /CO, lower heating value and cold gas efficiency, founding errors of 7.8%, 11.8% and 8.8% respectively. Additionally, the sensibility of the model to predict the effect of process variables as torrefaction temperature and equivalence ratio on response variables, showed similar tendencies to those found Cita: Suárez L, Pérez JF, Barrera R. Gasificación de madera para la obtención de un syngas útil en la producción de biocombustibles y/o productos químicos. rev.ion. 2017;30(1):57-71.

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Section: Descripción Del Modelounclassified

Section: Introductionunclassified

Gasificación de madera para la obtención de un syngas útil en la producción de biocombustibles y/o productos químicos

Hernández

Bayer

Zapata

2017

rev.ion

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“…This choice reflects the recommendation of the Aspen Plus user manual. The Peng-Robinson equation of state with Boston-Mathias alpha function (PR-BM) was used in this study to estimate all physical properties of the conventional components in the pyrolysis process [23].…”

Section: Simulationmentioning

confidence: 99%

“…In this study, the non-condensable gases have been used for the heat, which drives the MGW pyrolysis process. As suggested by Ramzan et al [23] and Kabir et al [25], the "RGIBBS" reactor model was used for condensable vapour combustion in the absence of air with the assumption that volatile reactions follow the Gibbs free energy equilibrium. It was assumed that the total yield of volatile products was equal to the volatile content of the green waste and that all the sulphur in the green waste reacts with H2 to form H2S.…”

Section: Simulationmentioning

confidence: 99%

Pyrolysis of Municipal Green Waste: A Modelling, Simulation and Experimental Analysis

2015

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Abstract:Pyrolysis is the thermo-chemical conversion of carbonaceous feedstock in the absence of oxygen to produce bio-fuel (bio-oil, bio-char and syn-gas). Bio-fuel production from municipal green waste (MGW) through the pyrolysis process has attracted considerable attention recently in the renewable energy sector because it can reduce greenhouse gas emissions and contribute to energy security. This study analyses properties of MGW feedstock available in Rockhampton city of Central Queensland, Australia, and presents an experimental investigation of producing bio-fuel from that MGW through the pyrolysis process using a short sealed rotary furnace. It was found from the experiment that about 19.97% bio-oil, 40.83% bio-char and 29.77% syn-gas can be produced from the MGW. Then, a four-stage steady state simulation model is developed for pyrolysis process performance simulation using Aspen Plus software. In the first stage, the moisture content of the MGW feed is reduced. In the second stage, the MGW is decomposed according to its elemental constituents. In the third stage, condensate material is separated and, finally, the pyrolysis reactions are modelled using the Gibbs free energy minimisation approach. The MGW's ultimate and proximate analysis data were used in the Aspen Plus simulation as input parameters. The model is validated with experimentally measured data. A good OPEN ACCESSEnergies 2015, 8 7523 agreement between simulation and experimental results was found. More specifically, the variation of modelling and experimental elemental compositions of the MGW was found to be 7.3% for carbon, 15.82% for hydrogen, 7.04% for nitrogen and 5.56% for sulphur. The validated model is used to optimise the biofuel production from the MGW as a function of operating variables such as temperature, moisture content, particle size and process heat air-fuel ratio. The modelling and optimisation results are presented, analysed and discussed.

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“…Moreover, this technology can significantly reduce the volume of biomass waste generated in developing societies [1]. Gasification is a thermo-chemical conversion which converts solid fuel such as biomass into useful synthesis gas (mixture of CO, H 2 , and CH 4 ) through partial oxidation.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Steam Gasification in a Fluidized Bed Reactor with Energy Self-Sufficient Condition

Suwatthikul¹,

Limprachaya²,

Kittisupakorn³

et al. 2017

Energies

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Abstract:The biomass gasification process is widely accepted as a popular technology to produce fuel for the application in gas turbines and Organic Rankine Cycle (ORC). Chemical reactions of this process can be separated into three reaction zones: pyrolysis, combustion, and reduction. In this study, sensitivity analysis with respect to three input parameters (gasification temperature, equivalence ratio, and steam-to-biomass ratio) has been carried out to achieve energy self-sufficient conditions in a steam gasification process under the criteria that the carbon conversion efficiency must be more than 70%, and carbon dioxide gas is lower than 20%. Simulation models of the steam gasification process have been carried out by ASPEN Plus and validated with both experimental data and simulation results from Nikoo & Mahinpey (2008). Gasification temperature of 911 • C, equivalence ratio of 0.18, and a steam-to-biomass ratio of 1.78, are considered as an optimal operation point to achieve energy self-sufficient condition. This operating point gives the maximum of carbon conversion efficiency at 91.03%, and carbon dioxide gas at 15.18 volumetric percentages. In this study, life cycle assessment (LCA) is included to compare the environmental performance of conventional and energy self-sufficient gasification for steam biomass gasification.

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Simulation of hybrid biomass gasification using Aspen plus: A comparative performance analysis for food, municipal solid and poultry waste

Cited by 276 publications

References 17 publications

Gasificación de madera para la obtención de un syngas útil en la producción de biocombustibles y/o productos químicos

Gasificación de madera para la obtención de un syngas útil en la producción de biocombustibles y/o productos químicos

Pyrolysis of Municipal Green Waste: A Modelling, Simulation and Experimental Analysis

Simulation of Steam Gasification in a Fluidized Bed Reactor with Energy Self-Sufficient Condition

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