Development of generalised model for grate combustion of biomass

This project has been divided into two main parts, one of which has focused on modelling and one on designing and constructing a grate fired biomass test rig. The modelling effort has been defined due to a need for improved knowledge of the transport and conversion processes within the bed layer for two reasons: 1) to improve emission understanding and reduction measures and 2) to improve boundary conditions for CFD-based furnace modelling.The selected approach has been based on a diffusion coefficient formulation, where conservation equations for the concentration of fuel are solved in a spatially resolved grid, much in the same manner as in a finite volume CFD code. Within this porous layer of fuel, gas flows according to the Ergun equation. The diffusion coefficient links the properties of the fuel to the grate type and vibration mode, and is determined for each combination of fuel, grate and vibration mode. In this work, 3 grates have been tested as well as 4 types of fuel, drinking straw, wood beads, straw pellets and wood pellets. Although much useful information and knowledge has been obtained on transport processes in fuel layers, the model has proved to be less than perfect, and the recommendation is not to continue along this path. New visual data on the motion of straw on vibrating grates indicate that a diffusion governed motion does not very well represent the transport. Furthermore, it is very difficult to obtain the diffusion coefficient in other places than the surface layer of the grate, and it is not likely that this is representative for the motion within the layer. Finally, as the model complexity grows, model turnover time increases to a level where it is comparable to that of the full furnace model.In order to proceed and address the goals of the first paragraph, it is recommended to return to either a walking column approach or even some other, relatively simple method of prediction, and combine this with a form of randomness, to mimic the chaotic motion evident from full scale operation of grate fired plants. It is believed that such an approach will be a significant improvement to the current knowledge, without the drawbacks of the modelling approach attempted in this work.The second part of the project has been very successful. A fully operational, 500kWth multifuel facility has been designed, constructed and tested, and is now ready for future activities. The unit is big enough to represent real, full scale conditions, and yet small enough to be operational in terms of parameter studies of different nature. Apart from full SRO data, measurements (gas sampling, velocity, temperature, particle sampling) can be taken through a heated, water-cooled probe in the freeboard area along the length of the grate, and at several stations along the flue gas path up to the economizer. Data processing systems include FTIR, LDA and mass spectroscopy. This final report will be supplemented by a PhD report expected in the late summer of 2007, covering the modelling and experimental parts of the work. This project has been divided into two main parts, one of which has focused on modelling and one on designing and constructing a grate fired biomass test rig. The modelling effort has been defined due to a need for improved knowledge of the transport and conversion processes within the bed layer for two reasons: 1) to improve emission understanding and reduction measures and 2) to improve boundary conditions for CFD-based furnace modelling.The selected approach has been based on a diffusion coefficient formulation, where conservation equations for the concentration of fuel are solved in a spatially resolved grid, much in the same manner as in a finite volume CFD code. Within this porous layer of fuel, gas flows according to the Ergun equation. The diffusion coefficient links the properties of the fuel to the grate type and vibration mode, and is determined for each combination of fuel, grate and vibration mode. In this work, 3 grates have been tested as well as 4 types of fuel, drinking straw, wood beads, straw pellets and wood pellets. Although much useful information and knowledge has been obtained on transport processes in fuel layers, the model has proved to be less than perfect, and the recommendation is not to continue along this path. New visual data on the motion of straw on vibrating grates indicate that a diffusion governed motion does not very well represent the transport. Furthermore, it is very difficult to obtain the diffusion coefficient in other places than the surface layer of the grate, and it is not likely that this is representative for the motion within the layer. Finally, as the model complexity grows, model turnover time increases to a level where it is comparable to that of the full furnace model.In order to proceed and address the goals of the first paragraph, it is recommended to return to either a walking column approach or even some other, relatively simple method of prediction, and combine this with a form of randomness, to mimic the chaotic motion evident from full scale operation of grate fired plants. It is believed that such an approach will be a significant improvement to the current knowledge, without the drawbacks of the modelling approach attempted in this work.The second part of the project has been very successful. A fully operational, 500kWth multifuel facility has been designed, constructed and tested, and is now ready for future activities. The unit is big enough to represent real, full scale conditions, and yet small enough to be operational in terms of parameter studies of different nature. Apart from full SRO data, measurements (gas sampling, velocity, temperature, particle sampling) can be taken through a heated, water-cooled probe in the freeboard area along the length of the grate, and at several stations along the flue gas path up to the economizer. Data processing systems include FTIR, LDA and mass spectroscopy. This final report will be supplemented by a PhD report expected in the late summer of 2007, covering the modelling and experimental parts of the work.