Review and analysis of biomass gasification models

Puig-Arnavat, Maria; Bruno, Joan Carles; Coronas, Alberto

doi:10.1016/j.rser.2010.07.030

Cited by 688 publications

(348 citation statements)

References 68 publications

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“…The kinetic rate models are more accurate and computationally intensive. However, their applicability is limited to specific plants (Puig-Arnavat et al, 2010). Most of the chemical process simulation tools like Aspen Plus which build up a model from the first principle's approach have a higher computational burden.…”

Section: Methods Of Genetic Programming Modellingmentioning

confidence: 99%

“…Biomass gasification is a complex thermochemical process (Puig-Arnavat et al, 2010). In the recent past, numerous researchers have tried to simulate a realistic gasification process and optimized the process analysis to make it more cost effective.…”

Section: Introductionmentioning

confidence: 99%

“…In general, mathematical models are exploited to investigate the influence of the main process parameters on calorific value and yield of the product gas. Irrespective of the type of reactors, several modelling techniques such as thermodynamic equilibrium models, kinetic rate models, Aspen Plus based models and artificial neural networks have been implemented for gasification systems (Puig-Arnavat et al, 2010). The artificial intelligence techniques such as artificial neural networks, genetic programming etc.…”

Section: Introductionmentioning

confidence: 99%

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Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier

Pandey

Pan

Das

et al. 2015

Bioresource Technology

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A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalize well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based datadriven modelling strategy can be a good candidate for developing models for other types of fuels as well.

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Section: Methods Of Genetic Programming Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier

Pandey

Pan

Das

et al. 2015

Bioresource Technology

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“…This approach is independent of the gasifier type, being suitable to study the influence of operating parameters on the gaseous product composition of the process (PuigArnavat et al, 2010). According to Puig-Arnavat et al (2010), the largest discrepancies between predictions of equilibrium models and the corresponding values from actual gasification systems are found under low gasification temperatures. As a result, CO and H 2 contents are typically overestimated and CO 2 , CH 4 , tar and char contents are underestimated.…”

Section: Thermodynamic Equilibrium Modelingmentioning

confidence: 99%

Evaluation of Biomass and Coal Co-Gasification of Brazilian Feedstock Using a Chemical Equilibrium Model

Rodrigues

Muniz

Marcílio

2016

Braz. J. Chem. Eng.

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-Coal and biomass are energy sources with great potential for use in Brazil. Coal-biomass cogasification enables the combination of the positive characteristics of each fuel, besides leading to a cleaner use of coal. The present study evaluates the potential of co-gasification of binary coal-biomass blends using sources widely available in Brazil. This analysis employs computational simulations using a reliable thermodynamic equilibrium model. Favorable operational conditions at high temperatures are determined in order to obtain gaseous products suitable for energy cogeneration and chemical synthesis. This study shows that blends with biomass ratios of 5% and equivalence ratios ≤ 0.3 lead to high cold gas efficiencies. Suitable gaseous products for chemical synthesis were identified at biomass ratios ≤ 35% and moisture contents ≥ 40%. Formation of undesirable nitrogen and sulfur compounds was also analyzed.

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“…Thermodynamic equilibrium modeling offers simplicity and requires only chemical reaction equilibrium data. The equilibrium approach is not dependent on flow regime or mixing or residence time, and assumes that all the gas-phase shift reactions reach equilibrium, thereby overestimating syngas quality and carbon conversion (Puig-Arnavat et al, 2010). Chemical kinetic modeling requires more data (chemical kinetics, gasifier dimensions, and flow regime) and is more complicated.…”

Section: Model Developmentmentioning

confidence: 99%

Development of a chemical kinetic model for a biosolids fluidized-bed gasifier and the effects of operating parameters on syngas quality

Champion

Cooper

Mackie

et al. 2013

Journal of the Air & Waste Management Association

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In an effort to decrease the land disposal of sewage sludge biosolids and to recover energy, gasification has become a viable option for the treatment of waste biosolids. The process of gasification involves the drying and devolatilization and partial oxidation of biosolids, followed closely by the reduction of the organic gases and char in a single vessel. The products of gasification include a gaseous fuel composed largely of N 2 , H 2 O, CO 2 , CO, H 2 , CH 4 , and tars, as well as ash and unburned solid carbon. A mathematical model was developed using published devolatilization, oxidation, and reduction reactions, and calibrated using data from three different experimental studies of laboratory-scale fluidized-bed sewage sludge gasifiers reported in the literature. The model predicts syngas production rate, composition, and temperature as functions of the biosolids composition and feed rate, the air input rate, and gasifier bottom temperature. Several data sets from the three independent literature sources were reserved for model validation, with a focus placed on five species of interest (CO, CO 2 , H 2 , CH 4 , and C 6 H 6 ). The syngas composition predictions from the model compared well with experimental results from the literature. A sensitivity analysis on the most important operating parameters of a gasifier (bed temperature and equivalence ratio) was performed as well, with the results of the analysis offering insight into the operations of a biosolids gasifier.Implications: As gasification becomes a more prominent waste disposal option, understanding the effects of feedstock composition and gasifier parameters on the production of syngas (rate and quality) becomes increasingly important. A model has been developed for the gasification of dried sewage sludge that will allow for prediction of changes in syngas quality (and energy recovery from the waste), and should be helpful in assessing the benefits of new gasification projects. IntroductionGasification is the thermochemical conversion of organic feedstock into a synthetic gaseous fuel at high temperatures using a limited amount of air. The gaseous fuel produced by a gasifier is referred to as syngas or producer gas. Gasification lies between combustion and pyrolysis, and is a process that utilizes a substoichiometric amount of oxygen for partial oxidation of the feedstock. This in turn provides heat for the largely endothermic reduction reactions that produce the syngas, as well as the initial devolatilization of the biomass within the gasifier.Gasification is an efficient process for reducing the volume of waste, and is a process capable of delivering net energy gains (Greenhouse Gas Technology Center [GGTC], 2012; PuigArnavat et al., 2010). The remaining solids from the process are composed of the mineral ash that was contained in the feed and small amounts of organic ash, principally unreacted solid carbon (char). It is estimated that 7.2 million dry tons of sewage sludge are generated annually in the United States (North East Biosolids and Res...

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Review and analysis of biomass gasification models

Cited by 688 publications

References 68 publications

Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier

Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier

Evaluation of Biomass and Coal Co-Gasification of Brazilian Feedstock Using a Chemical Equilibrium Model

Development of a chemical kinetic model for a biosolids fluidized-bed gasifier and the effects of operating parameters on syngas quality

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