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Title: Investigation of biomass gasification processes for the production of high quality syngas
Author: Salem, Ahmed Morsy Mostafa
ISNI:       0000 0004 8503 3134
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 2020
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The gradual increase of fossil fuel depletion, as well as the harmful emissions associated with the increased global energy demand, has led to an increased effort to find new alternatives for energy production. Great attention has been placed on using renewable sources, which are clean and sustainable. Biomass, being one of the main sources for renewable energy, is a promising alternative to fossil fuels and can be converted to solid, liquid, and gaseous fuels using different technologies. As a result, many research works are being focused on the energy production from biomass. The most common use of biomass for energy is direct combustion, followed by gasification, carbonisation, and pyrolysis. Biomass gasification is preferred for energy production for many reasons; its availability everywhere and all over the year, the technology is simple to operate and maintain, and the valuable gaseous with by-products produced using gasification. A biomass gasifier must be designed based on experimentally or numerically trusted data for optimum energy production. Although experimental work is preferable, it is not always available; and undoubtedly, it is a cost and time intensive process. On the other hand, modelling can help in building up and designing biomass gasifiers and predicting the process of gasification based on a well-known validated dataset. Modelling can afford and study the gasification process considering the effect of varying working parameters, design, and fuel variations. Additionally, it is a cost-effective method that can be carried out in less time compared to experiments. However, the key challenges in economic and efficient design of a biomass gasifier often link with the biomass feedstock variety and hence their suitability for gasification. The wide variety of materials that can be used for gasification makes the design process complicated, because it depends on the feedstock type and required thermal power. Additionally, a biomass gasifier design has to deliver the highest possible production rate of syngas with its optimum gasification efficiency. These challenges are addressed in this thesis through an integrated research programme coupling novel modelling techniques with experiments. A detailed kinetic model is initially built to simulate and subsequently optimise the downdraft gasification process for typical biomass. However, it is found that the model is sensitive to the chemical contents of biomass feedstock. While particularly testing the model with agricultural waste feedstocks, it fails to predict the producer gas composition. Thus, more focus is given to improve the model's capability to accommodate and investigate the gasification process of Scottish agricultural feedstocks. The model is set through a series of chemical kinetic reactions at each zone of gasifier. The model is iterative and uses the previous zone's output as an input to the next zone to achieve higher accuracy compared to equilibrium and previous kinetic models. Further, a new approach for optimising the reduction zone length is developed in the model. The novel technique assumes all char to be consumed in the reduction zone. Gasifier design limitations and challenges are discussed, along with the identification of optimum process and design of a gasifier able to operate efficiently under numerous biomass materials. Tar content in producer gas limits its direct use and thus requires additional removal techniques. The modelling of tar formation, conversion and destruction along a gasifier could give a wider understanding of the process and help in tar elimination and reduction. Hence, more focus is applied to tar formation modelling inside the gasifier. A detailed kinetic model for the evolution and formation of tar from downdraft gasifiers, for the first-time, is built. The model incorporates four main tar species (benzene, naphthalene, toluene, and phenol), with a total of 20 different kinetic reactions implemented in the code for every zone, leading to greater accuracy and prediction of tar evolution, formation and cracking throughout the different zones of downdraft gasifiers compared to experiments. Experimental work is carried out to initially validate the results of the kinetic model and found a good agreement for wood biomass materials. Experiments are carried out at KTH Royal Institute of Technology, Sweden, and further used to validate the results from modelling process. The four main tar species are found to be a good representative for tar evolution in downdraft wood gasifiers, and in most cases, they form 50-90 % of the total tar produced. The producer gas predictions of the model are also found to be in good agreement over a wide range of feedstocks when comparing with various experimental data from literature for different moisture and equivalence ratios. Additionally, sensitivity analysis has been carried out to study the effect of varying moisture content and air equivalence ratio on the producer gas composition, tar content, and higher heating value. Furthermore, different gas and tar species distribution along the gasifier are discussed, along with the effect of changing working parameters. The input data to the model are the ultimate compositions of feedstock (CHNO), working conditions (e.g. moisture content and air equivalence ratio), and thermal power required. The model is built from scratch using MATLAB coding. A 2D computational fluid dynamics (CFD) model for downdraft biomass gasifiers is built using ANSYS software. The dimensions of the 2D model of a 20-kW downdraft gasifier and its design are based on the kinetic model results. The current model is tested against two different feedstocks and found a good agreement. One of the research aims is to validate the CFD model to cover a wide range of materials; biomass, waste, and agricultural residues such as wood, livestock beddings, and barley screenings. The novelty of the CFD model also includes the study of the formation and evolution of the four main tar species identified by the kinetic code. Mesh independency test is carried out using five different grids to choose the best grid for the simulations. The results of the tar species formation are validated against the kinetic and experimental data. Further novelty of the current CFD model is demonstrated through the prediction of gasification using different biomass, waste, and agricultural materials. Also, the model presents the tar species formation along the gasifier, which has not been discussed in any previously published works. The model also considers different tar and gas species formation along the gasifier centreline in both steady and unsteady states. Finally, the results obtained from the model conclude with the new findings of designing/optimising downdraft air-blown gasifiers including the production of high-quality syngas with low tar amounts.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral