Modelling of biomass milling

• Main Author: Newbolt, Gary S.
• Published: University of Nottingham 2018
• Subjects: TP Chemical technology
• Online Access: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.748470

Strategies to combat climate change focus on every industry and has led to government policies to reduce electricity generation through coal combustion. Switching to biomass provides an opportunity to use infrastructure constructed for coal combustion with carbon neutral fuels; however, the process of grinding biomass pellets as fuel in pulverised fuel combustion is not well known. 1% of energy generated at a power plant is utilised to achieve the required size for the fuel. Improvements in the understanding of biomass pellet milling could lead to optimisation of operating conditions and minimisation of energy consumption. The process could aid generators determine appropriate fuels and costs for each; this represents a potential opportunity to elongate the life of current power stations, which is more cost effective than construction of new biomass specific plants. This research has developed a population balance equation (PBE) model simulation to predict the output of biomass pellet grinding for Lopulco E1.6 mill and a Retsch PM100 planetary ball mill; this has never been published in literature. It has proven it can predict the output particle size distribution of a Lopulco E1.6 mill, a scale model of an industrial mill, for biomass pellet PSD’s. It has shown that the simulation parameters can be based on axial and flexure deformation testing results, and that it can predict the PSD to within an average 88% accuracy against blind test. A novel technique in evaluating a PSD has been achieved using an overlapping coefficient, a measure better suited to PSD analysis than conventional model validation techniques. The PBE simulation has also shown that back calculating parameters can separate mill and material contributions when utilising a popularly used selection function and a breakage function developed in this research based on the Rosin-Rammler equation. This has been shown for the Lopulco mill and a lab scale planetary ball mill for axial and flexure deformation tests respectively. The research shows that emphasis should be placed on understanding classifier dynamics due to unexpected behaviour in the Lopulco mill experiments. Further conclusions show that energy consumption can be related to axial deformation energy that can be explained by the action of a Lopulco mill’s application of compressive force on and the orientation of pellets against the rollers.