CHEMICAL ENGINEERING TRANSACTIONS VOL. 45, 2015 A publication of The Italian Association of Chemical Engineering www.aidic.it/cet Guest Editors: Petar Sabev Varbanov, Jiří Jaromír Klemeš, Sharifah Rafidah Wan Alwi, Jun Yow Yong, Xia Liu Copyright © 2015, AIDIC Servizi S.r.l., ISBN 978-88-95608-36-5; ISSN 2283-9216 DOI: 10.3303/CET1545186 Please cite this article as: Arora P., Hoadley A., Mahajani S.M., Ganesh A., 2015, Modelling and optimisation of dual fluidisation bed gasifiers for production of chemicals, Chemical Engineering Transactions, 45, 1111-1116 DOI:10.3303/CET1545186 1111 Modelling and Optimisation of Dual Fluidisation Bed Gasifiers for production of chemicals Pratham Arora a *, Andrew Hoadley b , Sanjay M. Mahajani c , Anuradda Ganesh d a IITB-Monash Research Academy, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India b Department of Chemical Engineering, Monash University, Clayton, VIC-3168, Australia c Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India d Department of Energy Science and Eng., Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India pratham.arora@monash.edu Biomass gasification is used in a variety of processes that range from heating application to the production of chemicals. Dual Fluidised Bed Gasifiers (DBFG), with their efficient operation and clean output syngas, are being proposed for many such applications. However, each application has a specific input syngas quality requirement. The quality of the syngas is a function of the biomass feedstock used, the gasifier technology employed, and the gasification conditions. A gasifier model can serve as an effective tool in the understanding of the effect of different parameters on the quality and quantity of syngas. Furthermore, these parameters could also be optimised to systematically meet the requirement of syngas. This study presents a kinetic-based compartment model for DBFGs that are developed in ASPEN Plus®. The model takes into account devolatisation, catalytic and homogenous gasification reactions for syngas and tars (using a lumped species approach); it also considers combustion of char and heat transfer through bed circulation. The model results were found to be in good agreement when compared with the operational data of an 8 MW CHP gasifier in Gussing, Austria. Furthermore, Multi-Objective Optimisation using the NSGA-II algorithm was also performed for the DBFG model. The optimisation aim was to derive a set of process conditions that are most favourable for the production of ammonia from syngas. 1. Introduction Biomass gasification is seen as one of the front runners for sustainable utilisation of bio-energy. Many technologies for biomass gasification have been proposed; the prominent ones are the updraft gasifier, the downdraft gasifier, the bubbling fluidised bed gasifier, the circulating fluidised bed gasifier and entrained flow gasification. Apart from these, many other technologies have been proposed, based on the combination of the prominent ones. The relative advantages of each technology are related to the biomass that has been gasified, the scale of gasification and the syngas quality required. This study focusses on understanding the working of the Dual Fluidised Bed Gasification (DFBG) technology. As its name suggests, two fluidised beds are used to carry out gasification and combustion separately. The gasification is carried out with steam, and air is used to sustain the combustion reactions. The heat transfer takes place through the circulation of hot bed material between the two beds. Since the gasification is carried out with steam, the nitrogen and tar content in the output syngas is quite low. A wide range of feedstocks can be gasified due to the compact design and easy feeding—requiring little pre-treatment of the biomass. Additionally, the gasifiers are known for their low investment costs. The use of bed material as a catalyst, in the application of chemical loop combustion, and in absorption-enhanced reforming has also been proposed (Göransson et al., 2011). The presence of a large number of gasification configurations makes it difficult to choose the best one for fulfilling the aims of a particular process. The construction of different lab-scale models would not only consume time and energy but might also not be economically feasible. To overcome these problems, researchers in the past have relied on simulation models to predict the syngas output for particular process configurations. The simulation models for biomass gasification can be grouped under four major methodologies, namely, the equilibrium model, the kinetic model, the Computational Fluid Dynamic (CFD)