Conference paper

Thermo economic analysis for the optimal conceptual design of biomass gasification energy conversion systems

This study addresses the thermo economic assessment of a biomass gasification, gas cleaning and energy conversion process, with particular attention given to tar control and the communication of the process design rationale. Product distributions were estimated with a parametric stoichiometric equilibrium model, derived from air gasification data. A multi- objective optimisation problem was defined for a superstructure of energy flow diagrams encompassing several alternatives for each processing step. The trade-off between total investment costs and the exergy efficiency of electricity production was obtained, and analysed to identify operating conditions that minimise tar formation so as to prevent equipment fouling. The use of air, oxygen or steam fluidised bed gasifiers, closed coupled to an internal combustion engine combined cycle (ICE-CC) requiring cold gas cleaning, or gas turbine combined cycle (GT-CC) requiring hot gas cleaning have been considered. Optimisation results suggest that the trade-off for steam gasification is the best (maximum efficiency found for ICE-CC at 34%, minimum cost for GT-CC at 14.3M€ for a plant capacity of 20 MWth,wood). However, results also indicate that further adaptation of the reaction model is necessary to properly assess product formation for other oxidants than air. For air gasification, maximum efficiency is obtained with ICE-CC (33%) and minimum costs for GT-CC at 17.1M€, and reaction model interpolation results are satisfactory. The optimal conditions for ICE-CC (low pressure and high temperatures) also favour minimal tar formation. Lastly, the formulation of this optimisation superstructure has been documented with an Integration Definition Function Modelling (IDEF0) activity model, by use of a "Plan Do Check Action" modelling template, to record and communicate the rationale of this conceptual design problem by gradual exposition of detail. This provides an explicit representation of preliminary design problem requirements, and also facilitates the interpretation of results and the detailed planning of subsequent design phases.


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