Development Models of Stoichiometric Thermodynamic Equilibrium for Predicting Gas Composition from Biomass Gasification: Correction Factors for Reaction Equilibrium Constants

Author:

Suparmin Prayudi12ORCID,Nelwan Leopold Oscar3ORCID,Mardjan Sutrisno S.3ORCID,Purwanti Nanik3ORCID

Affiliation:

1. Doctoral Program in Agricultural Engineering, IPB University, Bogor P.O. Box 220, West Java, Indonesia

2. Department of Mechanical Engineering, Institut Teknologi PLN, Menara PLN, Jalan Lingkar Luar Barat, West Jakarta 11750, Jakarta, Indonesia

3. Department of Mechanical and Biosystem Engineering, IPB University, Bogor P.O. Box 220, West Java, Indonesia

Abstract

A complex thermochemical process during biomass gasification includes many chemical reactions. Therefore, a stoichiometric model can be applied to predict the composition of the producer gas during gasification. However, the prediction of methane and hydrogen gas is still limited by a significant margin using the present stoichiometric models. The purpose of this research was to develop novel stoichiometric models that account for the reaction equilibrium constant with correction factors. The new models would enable forecasting of the composition of CO, CO2, CH4, H2, N2, tar, lower heating value (LHV), and cold gasification efficiency (CGE). Model development consisted of two stages, whereas the development of the models and their validation adopted an artificial neural network (ANN) approach. The first stage was calculating new correction factors and defining the new equilibrium constants. The results were six stoichiometric models (M1–M6) with four sets of correction factors (A–D) that built up the new equilibrium constants. The second stage was validating the models and evaluating their accuracy. Validation was performed by the Root Mean Square Error (RMSE), whereas accuracy was evaluated using a paired t-test. The developed models predicted the composition of the producer gas with an RMSE of less than 3.5% and ΔH-value of less than 0. The models did not only predict the composition of the producer gas, but they also predicted the tar concentration. The maximum tar concentration was predicted by M2C with 98.733 g/Nm3 at O/C 0.644, H/C 1.446, ER 0.331, and T 923 K. The composition of producer gases (CO, CO2, H2, and N2) was accurately predicted by models M1D, M2C, and M3C. This research introduces new models with variables N/C, O/C, H/C, ER, and T to simulate the composition of CO, CO2, CH4, H2, N2, and LHV-gas, with R2 > 0.9354, tar (C6H6)-R2 of 0.8638, and CGE-R2 of 0.8423. This research also introduces correction factors and a new empirical correlation for the reaction equilibrium constants in new stoichiometric models using steam reforming.

Funder

Institut Teknologi PLN Jakarta

Publisher

MDPI AG

Reference83 articles.

1. Small-Scale Biomass Gasification Systems for Power Generation (<200 kW Class): A Review;Situmorang;Renew. Sustain. Energy Rev.,2020

2. Biomass for Dual-Fuel Syngas Diesel Power Plants. Part I: The Effect of Preheating on Characteristics of the Syngas Gasification of Municipal Solid Waste and Wood Pellets;Suparmin;Arab. J. Basic. Appl. Sci.,2023

3. Thermodynamic Equilibrium Model Based on Stoichiometric Method for Biomass Gasification: A Review of Model Modifications;Silva;Renew. Sustain. Energy Rev.,2019

4. Performance Characterization of Waste to Electric Prototype Uses a Dual Fuel Diesel Engine and a Multi-Stage Downdraft Gasification Reactor;Sudarmanta;Mater. Sci. Forum,2019

5. Development of a Semi-Empirical Model for Woody Biomass Gasification Based on Stoichiometric Thermodynamic Equilibrium Model;Silva;Energy,2022

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