Energy & Fuels, Vol.27, No.12, 7398-7412, 2013
Modeling of a Biomass Gasification CHP Plant: Influence of Various Parameters on Energetic and Exergetic Efficiencies
This paper presents a theoretical assessment of energy, exergy, and syngas cleaning performances in a biomass gasification combined heat and power (CHP) plant with varying operating parameters. The analysis is carried out using a detailed model of a biomass gasification CHP plant developed with Aspen Plus. The model describes: wood drying and gasification in a dual fluidized bed (DFB) reactor, syngas cleaning, as well as combustion in a gas engine for electricity production. Heat is recovered from the CHP system for internal needs and for district and domestic water heating. An accurate prediction of tar and inorganic contaminants is developed for proper modeling of syngas cleaning efficiency. The influence of wood moisture content, drying conditions, flow rate of the sand circulating in the DFB reactor, catalyst and scrubbing agent efficiencies, as well as additional electricity production through steam turbine on the overall process performances is studied. On the basis of the comparative analysis of nine case studies, it is found that the highest energetic efficiencies are obtained when forced drying is not implemented in the CHP system. Lowering the inlet wood moisture content with natural drying (energy-free) prior to the CHP plant improves the electrical efficiency. An overall energetic efficiency of 74% (23% electric, 51% thermal; based on the lower heating value of wood on anhydrous basis) is then reached with wood fed at 30% moisture content. The best exergetic efficiency is reached when wood (naturally dried to 30%) is dried further to 15% by forced drying in the CHP plant and when some of the high-temperature heat is recovered for electricity production via steam turbine instead of district heating. In this case, the overall energetic efficiency is 63% (32% electric, 31% thermal). This model is a useful tool to assess process design improvements and life cycle inventory.