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The rapid depletion of conventional fossil fuels from the earth, and ever-growing demands for power generations, force the entire industrial world to search for new fuels that can replace the conventional fossil fuels. Also, an abundance amount of greenhouse gas emissions into the atmosphere like carbon dioxide, oxide of nitrogen, etc., are responsible for a consistent increase in environmental temperature, leading us to explore a reliable and efficient alternative fuel. One example of this alternative fuel is bio-derived synthetic gas (Syngas), produced by biomass gasification process. However, lower heat content and incombustible species content in the fuel makes Syngas challenging for gas turbines. In the proposed work, several experiments were carried out with fossil fuels (A.T.F., Diesel, etc.) for initial characterization of the micro gas turbine to investigate the performances such as TIT, the mass flow rate of fuel, and air, turbine output power/thrust. A thermodynamic and energy equilibrium analysis has been carried out for different alternative fuels (S.G., P.G., B.F.G.) to achieve the same TIT and power output for micro gas turbines. It is observed from the analysis that Syngas is the most promising fuel compared to other fuels for use in the gas turbine. For the same amount of fuel supply, only 7% power derating is dictated. That derating can be further reduced by an additional amount of fuel supply and by little modification of the gas turbine combustor. A simple five elements (4 PSR’s -Perfectly stirred reactor and 1 PFR – Plug flow reactor) gas turbine reactor network is proposed in the current analysis for the Syngas combustion in the gas turbine engine. The reactor network analysis presents a mechanism for different regions of a gas turbine combustor. In the reactor network, four PSR reactors serves as the different regions of the gas turbine combustor, i.e., Primary, Secondary, Dilution and Recirculation zones and the post flame zone simulated by PFR. The proposed reactor network predicts turbine inlet temperature in the range of overall equivalence ratios of 0.23-0.43. From the network analysis it has been well understood that, the energy and mass flow distributions required in a gas turbine combustor when fuelled with Syngas., Proceedings of the 30th European Biomass Conference and Exhibition, 9-12 May 2022, Online, pp. 717-720

Lignocellulosic residues have a resource base of 200 BT. However, the resource base is spread and wide diversity exists in lignocellulose (~12,570 angiosperms and gymnosperms). The diversity of the lignocellulose confers significant variation in degradation behaviour and gas production during anaerobic digestion (AD). Behaviour generalization and reactor designing for AD of lignocellulose fed reactors are therefore difficult. Utilization of the lignocellulose resource pool for biogas production mandates a parameter/criterion for fast selection of feedstock for use in AD and an estimate of achievable methane yield. A general prediction parameter for use with both monocots and dicots is, therefore, necessary. This study attempted to formulate a potential prediction parameter for the bio-methanation potential (BMP) using 9 lignocellulosic species (5 dicots and 4 agro residues). The study proposes, that the lag phase in methane (LPM), and biogas (LPB), and a dimensionless parameter formulated from the composition ‘(......+......+..+....)’, can be used to predict the methane yield (HWE= hot water extractives, Ox – oxalate extractives, HC=hemicellulose, C=cellulose, L=lignin). The study concluded that lignocellulosics which confers ............ ratio of 1.16, corroborated to methane yield greater than 338 l/kg VS, and are hence likely to be better feedstocks for bio-methane production., Proceedings of the 30th European Biomass Conference and Exhibition, 9-12 May 2022, Online, pp. 823-831

The article reports an extensive experimental investigation of the biomass combustion process and the factors affecting it. The study is initiated in a backdrop of the limited information available in literature towards characterizing a biomass combustion process with readily observable and measurable properties. The scope of the current work addresses the lacuna in the literature by studying the influence of particle size (10 mm – 20 mm), particle shapes, particle density (160 kg/m3 – 350 kg/m3), temperature (673 K – 1073 K) and oxidizer velocity (0.1 m/s – 10 m/s) on the biomass conversion process. The absolute biomass combustion time is split into pyrolysis (flaming time) and char oxidation time (glowing time), considering that the parameters have distinct influences on either process. It is observed that the particle size has a near-quadratic effect on both pyrolysis and char oxidation. The influence of sphericity and density on the combustion time is linear. Temperature influences the combustion time exponentially, and the combustion time is observed to decrease logarithmically with particle Reynolds number. The influence of various parameters on the combustion process is quantified by regression analysis. A correlation associating the combustion time with individual parameters is obtained. Further, the series of correlations are compounded to obtain the generic equations to estimate combustion time for a given set of parameters. The combustion time estimate from the equation is compared with experimental data from literature and found to be 10% deviation., Proceedings of the 30th European Biomass Conference and Exhibition, 9-12 May 2022, Online, pp. 667-669