Abstract:Energy recovery from biomass by gasification technology has attracted significant interest because it satisfies a key requirement of environmental sustainability by producing near zero emissions. Though it is not a new technology, studies on its integrated process simulation and analysis are limited, in particular for municipal solid waste (MSW) gasification. This paper develops an integrated fixed bed gasifier model of biomass gasification using the Advanced System for Process ENngineering (Aspen) Plus software for its performance analysis. A computational model was developed on the basis of Gibbs free energy minimization. The model is validated with experimental data of MSW and food waste gasification available in the literature. A reasonable agreement between measured and predicted syngas composition was found. Using the validated model, the effects of operating conditions, namely air-fuel ratio and gasifier temperature, on syngas production are studied. Performance analyses have been done for four different feedstocks, namely wood, coffee bean husks, green wastes and MSWs. The ultimate and proximate analysis data for each feedstock was used for model development. It was found that operating parameters have a significant influence on syngas composition. An air-fuel ratio of 0.3 and gasifier temperature of 700 °C provides optimum performance for a fixed bed gasifier for MSWs, wood wastes, green wastes and coffee bean husks. The developed model can be useful for gasification of other biomasses (e.g., food wastes, rice husks, poultry wastes and OPEN ACCESSEnergies 2013, 6 6509 sugarcane bagasse) to predict the syngas composition. Therefore, the study provides an integrated gasification model which can be used for different biomass feedstocks.

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Abstract:Gasification is a thermo-chemical process to convert carbon-based products such as biomass and coal into a gas mixture known as synthetic gas or syngas. Various types of gasification methods exist, and fluidized bed gasification is one of them which is considered more efficient than others as fuel is fluidized in oxygen, steam or air. This paper presents an experimental and numerical investigation of fluidized bed gasification of solid waste (SW) (wood). The experimental measurement of syngas composition was done using a pilot scale gasifier. A numerical model was developed using Advanced System for Process ENgineering (Aspen) Plus software. Several Aspen Plus reactor blocks were used along with user defined FORTRAN and Excel code. The model was validated with experimental results. The study found very similar performance between simulation and experimental results, with a maximum variation of 3%. The validated model was used to study the effect of air-fuel and steam-fuel ratio on syngas composition. The model will be useful to predict the various operating parameters of a pilot scale SW gasification plant, such as temperature, pressure, air-fuel ratio and steam-fuel ratio. Therefore, the model can assist researchers, professionals and industries to identify optimized conditions for SW gasification.

Fossil fuel-based energy sources are the major contributors to greenhouse gas (GHG) emission and thus the use of renewable energy (RE) is becoming the best alternative to cater for the increasing energy demand in both developing and developed nations. Chipendeke is a rural community in Zimbabwe, in which electricity demand is partially served by the only micro-hydro plant and hence, load shedding is a regular practice to keep essential services running. This study explored suitable opportunity to identify a feasible system with different energy sources that can fullfil the current and projected future load demand of the community. A techno-economic feasibility study for a hybrid RE based power system (REPS) is examined considering various energy sources and cost functions. Six different system configurations have been designed with different sizing combinations to identify the most optimum solution for the locality considering techno-economic and environmental viability. The performance metrics considered to evaluate the best suitable model are; Net Present Cost (NPC), Cost of Energy (COE), Renewable Fraction (RF), excess energy and seasonal load variations. In-depth, sensitivity analyses have been performed to investigate the variations of the studied models with a little variation of input variables. Of the studied configurations, an off-grid hybrid Hydro/PV/DG/Battery system was found to be the most economically feasible compared to other configurations.

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