Meeting the ever-increasing energy demands in our planet where conventional sources of energy are finite and fast depleting, controlling adverse phenomena like climate change, soil erosion, greenhouse gas emission, ozone layer thinning and pollution will remain profound challenges until widespread adoption of sustainable sources of energy is achieved. The shift to a sustainable energy system cannot be complete without the contribution of biomass energy. Within the ecosystem of biomass energy, gasification is a thermochemical conversion process undertaken to obtain a high-quality product gas by increasing the low energy density of solid biomass. The product gas can be used in power applications or be converted to liquid fuels for transportation. Gasification is carried out at high temperatures (700-1500°C) by using a gaseous agent under sub stoichiometric conditions (R.A. Kersten & De Jong, 2015). The main non-condensable permanent gases obtained from gasification are CO, H2, CO2 and CH4. Use of allothermal gasifiers, whose working is based on the separation of combustion and gasification chambers within the gasifier, with heat supply for carrying out endothermic reactions, established via heat carrier or heat exchanger, have shown many advantages compared to the conventional gasifiers (Hofbauer & Materazzi, 2019). The mix-up of product gas and flue gas is avoided in this type of gasification. Secondly, while using air for biomass combustion, the nitrogen present in air reduces the quality of the end product by not participating in gasification, thus resulting in a diluted product gas. A high-quality product gas can be obtained from allothermal gasifiers without the need for establishing an expensive air separation unit, as required in case of conventional gasifiers. The 50 kWth Indirectly Heated Bubbling Fluidized Bed Steam Reformer (IHBFBSR) at Delft University of Technology (TU Delft) represents a new concept of allothermal gasification technology where heat required for the endothermic gasification reactions is provided by two radiant tube burners placed vertically inside the reactor, one at the top and one at the bottom. The aim of this research is to optimize and validate the kinetic model developed for the IHBFBSR by a former student, Maarten Kwakkenbos in Aspen Plus®. The optimization is carried out with the help of the several steps, described in the report. The optimized model is then validated by using the results of the gasification tests performed under various operational conditions by PhD Candidates Mara del Grosso and Christos Tsekos. The optimized model predicts the gas composition obtained from the IHBFBSR quite well. In addition to the yield of permanent gases, N2, H2O and tars concentration in the product gas, along with various gas ratios (CO/H2, CH4/H2, CO/CO2) from the model are compared with the experimental values and found to be in reasonable agreement. Moreover, key performance indicators such as carbon conversion (CC), cold gas efficiency (CGE) and overall efficiency (OE) are also evaluated from both model and experiments and compared. The error ranges for most of the parameters lie within the reported deviations observed in various gasifier models in literature. After the validation of the model, the possibility of recycling a fraction of the product gas to feed the burners in order to make the set up more sustainable is evaluated. Sensitivity analyses is performed by varying steam to biomass ratios (SB*), primary and secondary air flowrate to evaluate the best process conditions under which product gas obtained from the gasifier, after subsequent cleaning, can be used for methanol production based on the H2/CO ratio. The results indicate that a higher SB* and a higher secondary air flowrate can result in a H2/CO ratio closer to the desired value required for optimum methanol production. From the heat analysis performed for the model, a possibility of increasing the overall efficiency of the process by adding a bypass line in the gasifier setup is suggested to be explored. The master thesis concludes by answering the research questions and recommendations to improve the detailing and accuracy of the model.