Co-gasification of Coal and Solid Waste to Hydrogen Enriched-Syngas in a Fixed Bed Gasifier

Abstract

The economic growth of every nation around the globe is centred on energy. Energy can be harnessed from different sources using different conversion systems, but such systems should be sustainable. Liquid fuels such as petroleum and solid fuels (e.g. coal & biomass) are largely used for energy production. Energy recovery from these fuels is usually carried out using thermal chemical processes such as combustion, pyrolysis, and gasification systems. Out of the three technologies, gasification is considered the most attractive based on its efficiency and other qualities. In the gasification process, syngas is produced. It is necessary to produce syngas of high quality such as hydrogen-enriched syngas. Hydrogen-enriched syngas can be used in fuel cells, gas turbines and engines for electricity production. This type of gas burns with little gaseous emissions to the atmosphere, but its production is dependent on the type of fuel and process conditions, and energy conversion system employed. In South Africa, around 95 % of electric power production comes from coal, and the current reserve is projected to last not more than a century [8]. Secondly, the coal is fast depleting and generates a lot of gaseous emissions (e.g. CO2, NOX & SOX) that pose a huge threat to the environment. The emission of the aforementioned gases is a very serious issue in South Africa. Presently, some Carbon Capture and Storage (CCS) projects are on-going in the country, although the CCS is not the fuse of this study. The gasification of biomass waste and coal could assist in gaseous emission reduction. Similarly, large amounts of agricultural wastes (e.g. sugarcane bagasse, corn cob & pine saw dust) and other solid waste such as tyre are in abundance in SA. It is detailed in chapter 2. Majority of the wastes are disposed indiscriminately, hence resulting in environmental pollution. Importantly, the solitary gasification of biomass is very expensive considering the prices of biomass. Besides that, biomass produces large amount of tar hence, resulting in operational difficulties in the gasifier and end user facilities. In this study, co-gasification of coal and solid wastes is considered as a crucial alternative to addressing the aforementioned problems. Particularly, the feedstocks used for this study were coal, biomass (corn cob (CC), pine sawdust (PSD), sugarcane bagasse (SCB)) and waste tyre (WT) and were pre-treated by drying, milling, sieving, and torrefaction (coal was not torrefied). The fuel samples were blended with coal at different ratios as detailed in the thesis and used for the study. For the torrefaction process, the most viable torrefaction process conditions and feedstock were determined, while the torrefaction process model for the feedstocks were developed, using Response Surface Methodology (RSM) and Artificial Neural Network (ANN), respectively. The Performance efficiency of gasification systems was evaluated using experimental data obtained from a few gasifiers (e.g. entrained, fluidised, and fixed bed) operated at varied experimental conditions using blends of feedstocks (e.g. biomass, coal, waste tyre etc.). A backpropagation Levenberg Marquardt (L-M) and Bayesian Regularisation (BR) algorithms of ANN model with Multiple Input- Multiple Output (MIMO) and Multiple Input-Single Output (MISO) layer networks were considered. The results of the MIMO and MISO layer networks obtained from the L-M algorithm were better than that of BR algorithm which is in affirmation with some of the results found in the literature. For model result improvement, Input Variables Representation Technique-by-Visual Inspection Method (IVRT-VIM) and Output Variables Representation Technique-by-Visual Inspection Method (OVRT-VIM) were developed from the study. Estimation of the gaseous emissions and profits from biomass, tyre, and coal fired co-gasification CHP Plant using Artificial Neural Network (ANN) was carried out for 20-year investment period using South Africa (SA) and Nigeria as cases studies via Artificial Neural Network (ANN). Higher profits were obtained from South African feedstocks than that of Nigerian feedstocks due to cheaper price of SA coal WFO and WOFC, but the gaseous emissions (CO, NOX, & SO2) from the Nigerian fuels were lower than that of SA because of differences in compositions of the fuels. The potentials of biomass torrefaction in terms of profitability in a co-gasification CHP plant for a 20-year-investment period was carried out using blends of Coal + SCB, Coal + CC, and Coal + PSD with coal-to-biomass ratio of 50:50, 71:29, and 80:20, respectively. The two financial cases mentioned earlier were considered. Four investment terms including: (A) 1st–5th, (B) 5th– 10th, (C) 10th– 15th & (D) 15th– 20th and two operational cost models; with feedstock costing (WFC) and without feedstock costing (WOFC) were employed. An estimated profit of between USD5.9 million - USD6.5 million and USD7.8 - USD7.9 million was earned at the end of investment plan using WFC and WOFC, respectively. The Internal Rate of Return (IRR) was 5 ± 1 %/yr. and 7 ± 4 %/yr. based on South African electricity price of 0.14 $/c kWh, respectively. The parametric effect of process variables during torrefaction of coal/biomass/waste tyre blends using ANN and RSM models were studied. The variables considered were Higher Heating Value (HHV), Enhancement Factor (EF), and Sold Yield (SY). The most effective operating process conditions (in terms of blending ratio, temperature and torrefaction time: input variables) is of the order: 50:50 at 300 OC and 45 min > 50:50 at 250 OC and 30 min >50:50 at 200 OC and 45 min. Similarly, the most viable fuel follows the order of Coal + Torrefied PSD > Coal + Torrefied SCB > Coal + Torrefied CC and > Coal + Torrefied WT. Coal + Torrefied PSD has HHV of 28.27 % and an EF of 1.41. This corresponded to around 10 % increase in the HHV of the torrefied fuel when compared to the raw fuel and about 25.23% higher than the EF of Coal + Torrefied WT of 1.03. Based on the result of the EF of Coal +Torrefied waste tyre, upgrading of the fuel quality via torrefaction is not recommended. Furthermore, a comprehensive study on tar treatment techniques was carried out using tars produced from biomass and blends of biomass and coal employing biochar based and Ni-biochar based catalysts. Box Behnken Design of Experiment (DoE) method was used. A full quadratic regression model was used to develop a mathematical model for tar treatment based on the feedstocks studied. The Pine Sawdust-Biochar Catalyst (PSD-BC) and Nickel Pine Sawdust-Biochar Catalyst (Ni-PSD-BC) were the most effective in terms of tar treatment and with an average percentage amount of tar conversion of 89.76 and 96.73%, respectively. Ni-PSD-BC was more efficient for tar cracking than PSD-BC, but PSD-BC (waste base) may be more attractive if sustainability and cost effectiveness of precursors are considered. Co-gasification of coal and pine sawdust (PSD) to hydrogen enriched syngas in a fixed bed gasifier was carried out with catalyst (WCAT) at 900 OC and without catalyst (WOCAT), at 700, 800, and 900 OC, respectively. Coal-to-PSD ratio of 1:1 was used, while Nickel-pine sawdust-biochar (Ni-PSD-BC) and pine sawdust-biochar (PSD-BC) were employed as catalysts. The gases produced at 700, 800 & 900 OC using WOCAT cannot be used in fuel cells and gas turbines due to poor quality, while others produced at 900 OC WCAT, can be used in internal combustion engines and gas turbines, but unfortunately, have lower quality to be employed in fuel cells for electricity production. However, the study provides a method of beneficiation of the high ash content South African coal for energy production. The outcome of this study is also instrumental to energy security, efficiency and sustainability as well as waste management in South Africa, Nigeria and other parts of the globe. An assessment of the economic, energy and environmental viability of a 5 MW co- gasification power plant was carried out, using blends of coal and biomass, and two financial cases were considered namely: with feedstock costing (WFC) and without feedstock costing (WOFC). Feedstock profitability in the plant for energy production was evaluated. Equipment consisting was not considered. The power plant used 20,473,451.41 kg, 20,986,049.96 kg, 18,251,806.49 kg, and 15,276,277.85 kg of Coal + SCB, Coal + CC, Coal + PSD, and Coal + WT to produce the 5 MW and 5.56 MW electric and thermal power, annually. Coal + Torrefied PSD was the most profitable of the fuels studied. The use of Coal-to-PSD ratio of 4:1 for the power generation as against Coal-to-PSD blend ratio of 1:1 resulted to an annual loss of about ZAR6, 461,301.77 ($90,458,224.70) and ZAR123,782.47 ($1,732954.58) WFC and WOFC, respectively.