Simulation And Optimization Of A Biomass Chemical-Looping Gasification Process For Hydrogen Production

Biomass is one of the available renewable energy resources for the production of biopower, biofuels and biobased chemicals which have less emission and negative environmental impact, as well as beneficial socio-economic impacts to society. Hydrogen is one of the industrial elements in great demand and a clean, high efficient, secondary energy. An ideal way for biomass utilization is Chemical-Looping hydrogen technology, which is able to produce a rich stream of both hydrogen and CO2.However, due to biomass physical and chemical characteristics, low bulk and energy density, the logistics process, including collection, transportation, and energy conversion process have a great influence on the use of biomass. In this thesis, a model of biomass chemical-looping gasification process for hydrogen production was developed using mathematical modeling, discrete event modeling using EXTEND SIM7(?)(Imagine That Inc., San Jose, CA, USA) and chemical process simulation using ASPEN PLUS(?)(AspenTech Inc., Burlington, Massachusetts, USA) to established the fuel collection, transportation and plant production process models. The model was used to conduct a comprehensive simulation of the whole process, and the fuel logistics and process operation parameters were optimized.Firstly, a biomass logistics model was developed which simulated biomass supply from the field directly to the plant, for biomass that was close to the plant (Field-Plant) and biomass supply through a collection station, for biomass available far away from the plant (Field-Collection Station-Plant). A mathematical model based on previous work by Yu (2011) was developed to describe the primary logistics of transporting biomass from the field to collection stations. A theoretical square area around collection stations and the plant was used to approximate the collection field to estimate the logistics cost and CO2emissions. The secondary logistics model, from collecting station to plant, was built using the discrete event software EXTEND SIM7(?). The model took into account the moisture content of delivered biomass; dry biomass was transported directly for use while wet biomass (>45%wet basis) had to be routed through a dryer prior to utilization. The parameters such as average trip time of each truckload, average equipment waiting time and logistics equipment utilization were used to understand the logistics and cost of biomass to the hydrogen plant. The logistics of plant raw materials such as limestone and by-product ash was also simulated.The second aspect of this research was the development of the plant production process model using a chemical process simulation software, ASPEN PLUS(?). The plant Core process included gasification and combustion processes. The gasification process included pyrolysis and reforming modules, and the yield of each initial pyrolysis product was determined based on the results of pyrolysis experiments in which pressure and temperature effects were considered. Char produced in pyrolysis occurring in the gasifier was fed into the combustor so as to achieve the calcination temperature of calcium carbonate. The reforming and combustion processes were based on Gibbs free energy minimization approach. And the other process in the factory, such as air separation. Heat Recovery Steam Generator (HRSG), gas turbine and steam turbine were also simulated.Finally, the logistics of biomass and chemical processes for hydrogen were simulated for a2300t/d biomass consumption chemical-looping gasification process for hydrogen. Sensitivity analysis of the effect of varying amounts of equipment was conducted. The model was optimized to obtain minimum cost of biomass at all available times, while maximizing quantities of biomass obtainable during the short harvest window. The total CO2emission of the logistics system was also calculated. Sensitivity analyses of bed pressure, temperature and equivalence ratio of [Ca]/[C] and [H2O]/[C] were performed. Parameters were optimized using simulation to obtain the highest hydrogen production. The highest energy transformation efficiency was74.9%when the hydrogen production was210t/d, power supply was37.5MW, CO2emission was161.2t/d and hydrogen production efficiency was70.3%.