Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview

In this paper, the authors present an overview of biomass gasification modeling approaches with the aim of evaluating their effectiveness as a modeling tool for the design and optimization of polygeneration plants based on biomass gasification. In fact, the necessity to build plant operating maps fo...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Linda Moretti [verfasserIn] Fausto Arpino [verfasserIn] Gino Cortellessa [verfasserIn] Simona Di Fraia [verfasserIn] Maria Di Palma [verfasserIn] Laura Vanoli [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	gasification biomass syngas modeling equilibrium model stoichiometric

Übergeordnetes Werk:	In: Energies - MDPI AG, 2008, 15(2021), 1, p 61
Übergeordnetes Werk:	volume:15 ; year:2021 ; number:1, p 61

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/en15010061

Katalog-ID:	DOAJ023485531

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allfields	10.3390/en15010061 doi (DE-627)DOAJ023485531 (DE-599)DOAJ876730a2ff53463596e50a34575ac5f8 DE-627 ger DE-627 rakwb eng Linda Moretti verfasserin aut Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, the authors present an overview of biomass gasification modeling approaches with the aim of evaluating their effectiveness as a modeling tool for the design and optimization of polygeneration plants based on biomass gasification. In fact, the necessity to build plant operating maps for efficiency optimization requires a significant number of simulations, and non-stoichiometry equilibrium models may allow fast computations thanks to their relative simplicity. The main objective consists of the assessment of thermodynamic equilibrium models performance as a function of biomass type and composition to better understand in which conditions of practical interest such models can be applied with acceptable reliability. To this aim, the authors developed two equilibrium models using both a commercial software (referred as Aspen model) and a simulation tool implemented in a non-commercial script (referred as analytical model). To assess their advantages and disadvantages, the two models were applied to the gasification simulation of different biomasses, employing experimental data available from the scientific literature. The obtained results highlighted strengths and limitations of using equilibrium models as a function of biomass type and composition. For example, they showed that the analytical model predicted syngas composition with better accuracy for biomass types characterized by a low ash content, whereas the Aspen model appeared to fairly predict the syngas composition at different conditions of ER; however, its accuracy might be reduced if the properties of the treated biomass changed. gasification biomass syngas modeling equilibrium model stoichiometric Technology T Fausto Arpino verfasserin aut Gino Cortellessa verfasserin aut Simona Di Fraia verfasserin aut Maria Di Palma verfasserin aut Laura Vanoli verfasserin aut In Energies MDPI AG, 2008 15(2021), 1, p 61 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:15 year:2021 number:1, p 61 https://doi.org/10.3390/en15010061 kostenfrei https://doaj.org/article/876730a2ff53463596e50a34575ac5f8 kostenfrei https://www.mdpi.com/1996-1073/15/1/61 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 1, p 61
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allfieldsSound	10.3390/en15010061 doi (DE-627)DOAJ023485531 (DE-599)DOAJ876730a2ff53463596e50a34575ac5f8 DE-627 ger DE-627 rakwb eng Linda Moretti verfasserin aut Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, the authors present an overview of biomass gasification modeling approaches with the aim of evaluating their effectiveness as a modeling tool for the design and optimization of polygeneration plants based on biomass gasification. In fact, the necessity to build plant operating maps for efficiency optimization requires a significant number of simulations, and non-stoichiometry equilibrium models may allow fast computations thanks to their relative simplicity. The main objective consists of the assessment of thermodynamic equilibrium models performance as a function of biomass type and composition to better understand in which conditions of practical interest such models can be applied with acceptable reliability. To this aim, the authors developed two equilibrium models using both a commercial software (referred as Aspen model) and a simulation tool implemented in a non-commercial script (referred as analytical model). To assess their advantages and disadvantages, the two models were applied to the gasification simulation of different biomasses, employing experimental data available from the scientific literature. The obtained results highlighted strengths and limitations of using equilibrium models as a function of biomass type and composition. For example, they showed that the analytical model predicted syngas composition with better accuracy for biomass types characterized by a low ash content, whereas the Aspen model appeared to fairly predict the syngas composition at different conditions of ER; however, its accuracy might be reduced if the properties of the treated biomass changed. gasification biomass syngas modeling equilibrium model stoichiometric Technology T Fausto Arpino verfasserin aut Gino Cortellessa verfasserin aut Simona Di Fraia verfasserin aut Maria Di Palma verfasserin aut Laura Vanoli verfasserin aut In Energies MDPI AG, 2008 15(2021), 1, p 61 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:15 year:2021 number:1, p 61 https://doi.org/10.3390/en15010061 kostenfrei https://doaj.org/article/876730a2ff53463596e50a34575ac5f8 kostenfrei https://www.mdpi.com/1996-1073/15/1/61 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 1, p 61
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author	Linda Moretti
spellingShingle	Linda Moretti misc gasification misc biomass misc syngas misc modeling misc equilibrium model misc stoichiometric misc Technology misc T Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview
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topic_title	Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview gasification biomass syngas modeling equilibrium model stoichiometric
topic	misc gasification misc biomass misc syngas misc modeling misc equilibrium model misc stoichiometric misc Technology misc T
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title	Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview
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title_sort	reliability of equilibrium gasification models for selected biomass types and compositions: an overview
title_auth	Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview
abstract	In this paper, the authors present an overview of biomass gasification modeling approaches with the aim of evaluating their effectiveness as a modeling tool for the design and optimization of polygeneration plants based on biomass gasification. In fact, the necessity to build plant operating maps for efficiency optimization requires a significant number of simulations, and non-stoichiometry equilibrium models may allow fast computations thanks to their relative simplicity. The main objective consists of the assessment of thermodynamic equilibrium models performance as a function of biomass type and composition to better understand in which conditions of practical interest such models can be applied with acceptable reliability. To this aim, the authors developed two equilibrium models using both a commercial software (referred as Aspen model) and a simulation tool implemented in a non-commercial script (referred as analytical model). To assess their advantages and disadvantages, the two models were applied to the gasification simulation of different biomasses, employing experimental data available from the scientific literature. The obtained results highlighted strengths and limitations of using equilibrium models as a function of biomass type and composition. For example, they showed that the analytical model predicted syngas composition with better accuracy for biomass types characterized by a low ash content, whereas the Aspen model appeared to fairly predict the syngas composition at different conditions of ER; however, its accuracy might be reduced if the properties of the treated biomass changed.
abstractGer	In this paper, the authors present an overview of biomass gasification modeling approaches with the aim of evaluating their effectiveness as a modeling tool for the design and optimization of polygeneration plants based on biomass gasification. In fact, the necessity to build plant operating maps for efficiency optimization requires a significant number of simulations, and non-stoichiometry equilibrium models may allow fast computations thanks to their relative simplicity. The main objective consists of the assessment of thermodynamic equilibrium models performance as a function of biomass type and composition to better understand in which conditions of practical interest such models can be applied with acceptable reliability. To this aim, the authors developed two equilibrium models using both a commercial software (referred as Aspen model) and a simulation tool implemented in a non-commercial script (referred as analytical model). To assess their advantages and disadvantages, the two models were applied to the gasification simulation of different biomasses, employing experimental data available from the scientific literature. The obtained results highlighted strengths and limitations of using equilibrium models as a function of biomass type and composition. For example, they showed that the analytical model predicted syngas composition with better accuracy for biomass types characterized by a low ash content, whereas the Aspen model appeared to fairly predict the syngas composition at different conditions of ER; however, its accuracy might be reduced if the properties of the treated biomass changed.
abstract_unstemmed	In this paper, the authors present an overview of biomass gasification modeling approaches with the aim of evaluating their effectiveness as a modeling tool for the design and optimization of polygeneration plants based on biomass gasification. In fact, the necessity to build plant operating maps for efficiency optimization requires a significant number of simulations, and non-stoichiometry equilibrium models may allow fast computations thanks to their relative simplicity. The main objective consists of the assessment of thermodynamic equilibrium models performance as a function of biomass type and composition to better understand in which conditions of practical interest such models can be applied with acceptable reliability. To this aim, the authors developed two equilibrium models using both a commercial software (referred as Aspen model) and a simulation tool implemented in a non-commercial script (referred as analytical model). To assess their advantages and disadvantages, the two models were applied to the gasification simulation of different biomasses, employing experimental data available from the scientific literature. The obtained results highlighted strengths and limitations of using equilibrium models as a function of biomass type and composition. For example, they showed that the analytical model predicted syngas composition with better accuracy for biomass types characterized by a low ash content, whereas the Aspen model appeared to fairly predict the syngas composition at different conditions of ER; however, its accuracy might be reduced if the properties of the treated biomass changed.
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title_short	Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview
url	https://doi.org/10.3390/en15010061 https://doaj.org/article/876730a2ff53463596e50a34575ac5f8 https://www.mdpi.com/1996-1073/15/1/61 https://doaj.org/toc/1996-1073
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Reliability of Equilibrium Gasification Models for Selected Biomass Types and Compositions: An Overview

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