Detection of onset of agglomeration in a bubbling fluidized bed biomass combustor using reactive Eulerian computational fluid dynamics

Abstract

The choice of a type of combustion technology to be used for heat or power generation depends on economic, technical, operational and fuel availability constraints. The benefits associated with the evolving market driven by the fluidised bed combustion (FBC) technology cannot be overlooked especially when gauged at 65 GWth of worldwide installed capacity alongside added benefits of handling fuel variation, low pollutant emissions and high combustion efficiency. Biomass or biomass waste will continue to have a vital role to play in the future FBC technology-based power generation. Biomass often contains high levels of inorganic species that can form sticky agglomerates posing a significant risk to boiler operation resulting in unscheduled outages. This added complexity of the behaviour of the fuel and bed material mix highlights the requirement for simulation models to identify agglomeration to help improve the overall performance and reliability of FBC technology. To resolve this problem, this research devised a simulation strategy for the detection of agglomeration using the Eulerian–Eulerian approach. The developed modelling strategy is validated with the experimental data available in literature for two-dimensional simplified geometry of a pilot-scale fluidised bed combustor. The model results were found promising and robust to predict bed defluidisation times and other parameters consistent with the experimental data.