IN
DEGREE PROJECT MATERIALS SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS
STOCKHOLM SWEDEN 2018,
Process Simulation of Plasma Gasification for Landfill Waste
BOON HAU TAN
KTH ROYAL INSTITUTE OF TECHNOLOGY
Table of Contents
List of Figures ... I List of Tables ... II ABSTRACT ... III
1. INTRODUCTION ... 1
1.1 Background ... 1
1.2 Objective ... 4
1.3 Scope ... 4
2. LITERATURE REVIEW ... 5
2.1 Fine fraction ... 5
2.2 Aspen Plus Modelling ... 6
2.3 Plasma Gasification ... 12
2.4 Tar Cracking ... 14
2.5 Melting ... 16
3. METHODOLOGY ... 17
3.1 Plasma Gasification Process ... 17
3.2 Plasma Gasification Model ... 18
3.2.1 Feedstock properties ... 18
3.2.2 Drying ... 20
3.2.3 Pyrolysis ... 21
3.2.4 Char Combustion and Gasification ... 21
3.2.5 Melting ... 22
3.2.6 Plasma Tar Cracking ... 22
3.3 ASPEN Plus Model description ... 24
3.3.1 Assumptions ... 28
3.3.2 Boundary Conditions ... 28
3.4 Parameter Studies ... 29
4. RESULTS AND DISCUSSION ... 31
4.1 Verification and Validation of Model ... 31
4.1.1 Syngas Composition Pre and Post Tar Cracking ... 32
4.2 Mass and Energy Balance ... 33
4.3 Results of Parameter Studies ... 35
4.3.1 Effect of ER ... 35
4.3.2 Effect of Preheated Air Temperature ... 37
5. CONCLUSION ... 40
6. FUTURE WORK ... 41
7. REFERENCE ... 42
List of Figures
Figure 1. The role of plasma gasification in a circular economy. (Power, 2018) ... 3
Figure 2. Plasma gasification model of EPJ Model (Minutillo et al., 2009). ... 9
Figure 3. A two stage plasma gasification process (Materazzi et al., 2016). ... 12
Figure 4. Tar Cracking Model (Fourcault et al., 2010). ... 15
Figure 5. Comparison of required heat for incineration and gasification (Li et al., 2007). ... 16
Figure 6. Schematic of two stage plasma gasification model. ... 17
Figure 7. Simplified schematic of the plasma gasification model. ... 20
Figure 8. Flowsheet of plasma gasification process in Aspen Plus. ... 24
Figure 9. Comparison between syngas composition before and after tar cracking. ... 32
Figure 10. Mass and Energy Balance diagram for plasma gasification system. ... 33
Figure 11. Sankey diagram showing flow of energy for plasma gasification system. ... 34
Figure 12. Pie chart showing distribution of energy output. ... 35
Figure 13. Effect of increasing ER on syngas composition at Tpreheat air = 873K ... 36
Figure 14. Effect of increasing ER on LHV and CGE. ... 36
Figure 15. Heat of partial combustion required from air (ER = 0.208) at different Tpreheat air ... 38
Figure 16. Graph showing lowest possible ER at different Tpreheat air. ... 38
Figure 17. Effect of Tpreheat air on LHV and CGE according to lowest possible ER at each Tpreheat air. ... 39
List of Tables
Table 2. Material Composition of RDF ... 18
Table 3. Ultimate and proximate analyses of RDF ... 19
Table 4. Analyses of metal contents of RDF ... 19
Table 5. Char combustion and gasification reactions considered. ... 22
Table 6. Reactions considered for tar cracking. ... 23
Table 7. Description of unit operation blocks in ASPEN Plus flowsheet. ... 26
Table 8. Aspen Plus material streams. ... 27
Table 9. Aspen Plus heat streams. ... 28
Table 9. Boundary conditions for plasma gasification model. ... 29
Table 10. Parameters that were studied in the ASPEN Plus model. ... 30
Table 11. Comparison of composition between Aspen Plus Model and Similar Setup ... 31
Table 12. Mass balance of Aspen Plus model. ... 34
Table 13. Energy balance of Aspen Plus model. ... 34
ABSTRACT
The growing amount of landfill waste within the EU could pose a problem in the future should there not be any effective treatment methods. This study aims to investigate the performance of landfill waste in a plasma gasification process by simulating the process in ASPEN Plus. The investigation is focused on the energy recovery potential of RDF based on composition and heating value of syngas, and cold gas efficiency (CGE). The plasma gasification system consists of a shaft gasifier and a separate tar cracking reactor where high temperature plasma is used for conversion of tar compounds considered in the model, which are toluene and naphthalene.
In addition, the model is divided into five sections, namely drying, pyrolysis, char gasification, melting and tar cracking. Mass and energy balance of the system was performed to better understand the system. The results show that the plasma gasification system was able to produce a syngas with a LHV of 4.66 MJ/Nm3 while improving syngas yield by attaining a higher content of hydrogen. Thus, the plasma tar cracking of tar compounds can achieve a clean syngas and improve syngas yield. Parameter study on effect of ER show that syngas has higher heating value and CGE at lower ER. On the other hand, preheated air can help recover energy from the system while lowering the ER required for the char gasification process to meet the heat demand from partial combustion. The findings implied that landfill waste has energy potential by using a suitable treatment process such as plasma gasification.
Keywords: landfill waste, RDF, plasma gasification, syngas
1. INTRODUCTION
1.1 Background
Landfill has been traditionally the solution for all the wastes produced prior to invention of modern and advanced treatment methods. The consequence is the existence of an estimated 150,000 to 500,000 landfill sites within Europe that will have repercussions for years to come (Hogland et al., 2010). Throughout the decades, waste management has progress gradually towards a more sustainable path with focus on reduction in consumption, recycle of waste products, and waste valorization. State of the art technology is required to reduce landfill waste which can open up other opportunities.
Pertaining to landfilling, it has been included in ‘Roadmap to a Resource Efficient Europe’
documented by European Union (EU) that landfilling should be the final option and gradually be ruled out as a solution as part of their aim by 2020 to manage waste resources in a sustainable manner (Commission, 2011). This has led to two innovative concepts known as Enhanced Waste Management (EWM) and Enhanced Landfill Mining (ELFM) that attempt to address issues surrounding landfill waste. EWM emphasizes on reduction in usage and recycling, which rules out landfilling as the final destination but as a buffer storage to be processed after. On the other hand, ELM is an approach for waste valorization, where waste from both old and new landfills are used as source of materials and fuel for energy recovery process (Bosmans et al., 2013). Such concepts will be able to unlock potential in the vast amount of waste that have been buried and left to once again be precious resources that can be utilize for various applications. Furthermore, not only extravagant costs of remediation can be avoided, the land used for landfilling can attain a higher value by commercialized exploration and activities. A projected 0,1-1 trillion euro in the next 5 decades will be required as remediation costs for the EU-28 while the Flemish Public Waste Agency, OVAM was reported to have spent 80 million euro to remediate just 5 problematic landfills, by excavating landfilled material, transporting and re-landfilling in a modern sanitary landfill (Jones et al., 2013). There is however insufficient and less efficient usage of budget to perform such a scale of project for majority of states in EU (Vautmans, 2015).
Solid waste based energy recovery via incineration has been a common method used to treat municipal solid waste but also as source of electricity and heat. Waste incineration combust solid waste typically in the form as refused derived fuel (RDF) to obtain a more sustainable operation as well as to achieve a higher calorific value thus a higher electrical efficiency.
Conversion of municipal solid waste (MSW) into RDF involves possible mechanical and/or manual handling to obtain more homogeneous properties which enhances calorific value.
However, process and treatment varies according to landfill sites because of variation in waste properties and compositions. The downside of incineration being a complete oxidative combustion process is the need for expensive flue gas treatment equipment due to presence of SOx and NOx, disposal problems with fly ash and bottom ash that may cause potential hazard in leaching of heavy metals should it be reused. Advanced thermal treatment that turns bottom ash into environmentally friendly products is available but consumes a significant amount of energy that reduces energy recovery efficiency.
Gasification which is a partial oxidation process offers another alternative thermochemical process to treat solid wastes by converting into synthesis gas (syngas) that has calorific value and can be used as a fuel for various industries such as chemical industry and power generation. Different gasification agents such as air, oxygen can be used to produce syngas of higher calorific value using the latter. There has been development in using plasma technology with gasification where the high energy density from plasma can enhance reaction rate and at a higher temperature, materials can be melted into slag. Plasma gasification results in syngas with primarily carbon monoxide and hydrogen. At extreme high temperature, tar and char can be broken down thus having a cleaner syngas without expensive gas cleaning facilities. Meanwhile, hazardous inorganic materials can be vitrified in the molten slag without leaching issues. Thus, the gasification process can play an important role in achieving a circular economy as illustrated in Figure 1.
Figure 1. The role of plasma gasification in a circular economy. (Power, 2018)
Studies has been much on MSW, rather less on landfill waste. Landfill waste which are buried for years and decades undergoes decomposition which makes properties difficult to predict and it increase heterogeneity of the waste. The decomposition increases soil and fine fraction which may affect the energy recovery potential and also additional pre-treatment process is required before being used as a fuel. Preliminary studies have been conducted through experiments, modelling, and simulation but still require further investigation as there are still uncertainties in the landfill waste before investing in large scale plants.
There have been studies conducted on characterization of landfill waste using various plasma gasification technologies such as fixed bed, fluidizing bed and entrained flow. However, there are not many studies on two stage plasma gasification process comprising of a stand-alone gasifier and plasma tar converter. Presence of tar in the product gas makes it difficult for product gas to be used and additional costs may be required to clean up the gas for practical usage. A separate plasma tar converter has better potential in achieving higher tar conversion rate. Tars contained in the product gas can contribute to an increase in heating value of product gas. Tar is often not taken into account in simulation of gasification due to complexity of tar compounds and cracking process. Hence, this study intends to investigate the potential of landfill waste in energy recovery in terms of composition of product gas, energy value
considering tar compounds in the process and the efficiency of the gasification process. Firstly, some literature studies will be done to review the problematic content of the landfill waste.
Next, some previous investigations on modelling of gasification using ASPEN Plus will be reviewed, followed by a study on usage of plasma gasification and applications of tar cracking.
Then, gasification process will be broken down in distinct models before building a ASPEN Plus model based on the schematic of the gasification process. Using the model, mass and energy balance will be performed before conducting parameter studies.
1.2 Objective
The objective of this study is to understand the energy and mass balance of plasma gasification system for a landfill waste based on the process modelling, as well as predict the plasma gasification performance in terms of efficiency and syngas quality from its composition.
1.3 Scope
The scope of this project involves developing the model for plasma gasifier using ASPEN Plus by breaking down into individual sections. The model will then be verified by using the experimental data obtained from a pilot scale plasma gasifier of similar construction. Finally, simulation of landfill waste gasification shall be performed to obtain the optimum conditions for the gasification process by carrying out parameter study to investigate the effect of different parameters in terms of the efficiency of process and composition of the syngas.
2. LITERATURE REVIEW 2.1 Fine fraction
Earlier studies on energy recovery potential of landfill waste were carried out at various locations. Due to non-homogeneous properties of the excavated waste, they are required to be pre-processed via processes such as crushing, sieving and manual sorting before being utilized as RDF. The main concern in landfill waste is the significant amount of fine fraction that is partly due to the decomposition of waste which would affect the calorific value of syngas produced as shown in some studies.
In a study done at REMO landfill located at Houthalen-Helchteren, Belgium characterized each category of material in the waste post sieving process showed that the fine fraction(<10 mm) which is between 40 – 60% in weight from different locations of landfill has a calorific value between 2.2 – 4.8 MJ/kg (Quaghebeur et al., 2013), thereby showing some energy recovery potential of landfill waste. In another landfill located at Högbytorp, Sweden, 3 different size fractions of waste were results of screening process and medium-size fraction was hand sorted to extract more materials for energy recovery. For the fine fraction, a comparable low calorific value (1.7 MJ/kg) was also obtained by an investigation done by (Jani et al., 2016) for fine fraction below 10 mm. Thus, fine fraction appears to be one of the challenges in the waste-to-energy application which has to be overcome.
Removal of fine fraction is able to improve the calorific value. (Wanka et al., 2017) applied the principle of density to further separate fine fraction with the size fraction between 10 – 60 mm into 3 different fractions using a combination of water and mechanical treatment. The method is more efficient to extract RDF from fine fraction and remove fines attached to the RDF which will affect the calorific value subsequently energy recovery efficiency. Investigation carried out at two different landfill sites in Austria to evaluate the opportunity for resource recovery. Sieving of fine fraction to obtain higher recoverable fraction of waste suggested by (Wolfsberger et al., 2015). Contamination of heavy metals could affect the possibility of waste as RDF. Coarse fractions showed better energy recovery potential as shown in some studies.
Fine fraction in two landfills in Finland, one is aged between 1-10 years old and another
between 24-40 years old were mechanically separated defined with size below 20 mm and 30 mm were investigated of its properties such as Biochemical Methane Potential (BMP), volatile solids and total solids. It was discovered that BMP increases with size fraction. Besides, fine fraction increases with age due to greater decomposition of the waste (Monkare et al., 2016). (Kaartinen et al., 2013) suggested drying on the waste to remove fine fraction attached on calorific fraction. In the study, the waste was treated via manual sorting and mechanical treatment. However, investigated calorific value were of different size fractions, larger than 20 mm and 70 mm for manually sorted portion and mechanically treated portion respectively, the obtained calorific value was rather similar (20 – 25 MJ/kg). Similar findings by (Hogland et al., 2004) in fine fractions with calorific value between 0 – 1 MJ/kg, while in coarse fraction, it is feasible for energy recovery with a higher calorific value. Thus, drying appears to be able to improve the calorific value of the waste while making process more efficient as less energy is wasted on heating up water.
2.2 Aspen Plus Modelling
Numerous studies on modelling and simulation of gasification process has been performed using the process simulation software, Advanced System for Process Engineering (ASPEN) Plus since it is a more cost effective way to study the characteristic of different feedstocks used compared to a pilot plant scale. Parameter studies can also be done to investigate effect of different parameters on the process. Studies conducted using Aspen were widely applied for different feedstock and technology. Two different methods that can be used to simulate the model in Aspen, which are equilibrium and kinetic. Equilibrium based model are simulated by minimization of Gibbs free energy while kinetic based model takes into account reaction kinetics that occur. Equilibrium model can be used as a model that provides a broad picture of how a particular feedstock behaves in a process before detailed studies are carried out by considering more aspects.
Previous studies using equilibrium based model showed reasonable outcome as validated against experimental data and other studies. Crucial parameters such as Equivalence Ratio (ER), gasification temperature and steam addition are among others the common parameters
being investigated because of the significant influence on the energy recovery potential in the produced gas. (Niu et al., 2013) simulated gasification of municipal solid waste in a bubbling fluidized bed using the minimization of Gibbs free energy method and investigated the effect of Equivalence Ratio (ER), gasification temperature, moisture content, steam-waste ratio, and percentage of oxygen in air. It was discovered that for a higher syngas yield can be obtained at higher gasification temperature, an optimal ER of 0.3 at 800°C, higher percentage at lower temperature. Pre-drying of feedstock to a lower moisture to prevent extra energy to convert water to steam while higher steam-waste ratio facilitates for conversion to H2. Comparably, a circulating fluidized bed gasifier was simulated and the preheated air temperature was investigated over a range 25 – 825°C showed an increase in syngas heating value due to increase in H2 and CO. Furthermore, lesser volume of air is required to achieve a gasifier’s operating temperature can help to reduce the size of reactor which in turn is a savings to capital cost. Preheated air was found to be effective at lower ER, where a limit of 0.35 was recommended (Doherty et al., 2009). Similarly, influence of ER was also studied by (Li et al., 2013) in a simulation where an optimal preheated air temperature at 600°C with ER of 0.4 was also found out to be important for the gasification process. Meanwhile, an increase of ER led to a decrease in lower heating value (LHV) of syngas. Plasma gasification of three types of biomass, coffee husks, vines pruning and forest residues for hydrogen production were investigated. ER was varied between 0.1 – 0.6 and it was found that oxidation reactions was more prominent due to higher oxygen content thus decreasing H2 yield. At the same time, N2 content rises caused by increased in amount of air. Steam used as gasifying agent increased H2 yield by promoting water gas shift and steam reforming due to increased water vapor partial pressure (Favas et al., 2017). Gasifier temperature was varied from 900 – 2000°C and it was discovered that CO yield increased but H2 and CO2 was the opposite as water shift reactions are exothermic.
A fixed bed gasifier that used MSW as feedstock and results were compared to experimental data. The model was used to study the effect of air-fuel ratio and gasifier temperature. Results showed that optimum air-fuel ratio was around 0.3 and at higher gasifier temperature, yield of CO increased (Begum et al., 2014). A downdraft gasifier integrated with a power generation unit for different biomass fuels comprised of different woods was simulated with a model in
Aspen Plus using REquil reactor to compare the gasifier efficiencies. Simulation results were compared with experimental data and CH4 had a huge variance possibly due to very simple model built. Average calorific value obtained for the biomass fuels is about 18 MJ/kg (Keche et al., 2014).
Apart from air, steam is also used as a gasifying agent along with air to achieve a product gas with higher yield of hydrogen. Performance for gasification of MSW, food waste and poultry waste were compared to experimental data. Parameter studies lead to findings that showed higher temperature favors CO and H2 production and steam addition at an optimum range 0.15 – 0.3 for steam-to-biomass ratio can enhance H2 yield (Ramzan et al., 2011).Another model based on minimizing Gibbs free energy was designed to predict syngas composition using steam gasification of different biomass for Fischer-Tropsch synthesis. It was observed that increase in gasification temperature from 750 – 950 °C increases yield of CO but decreases the yield of CO2 and CH4 (Pala et al., 2017). Endothermic reactions are favorable as temperature increases driving chemical reaction to the right side. Meanwhile, steam addition benefited H2 and CO2 yield.
There are also studies that integrates the gasification process with other processes such as power generation. Plasma gasification of MSW and plastic solid waste at different blending ratio was simulated by (Mazzoni and Janajreh, 2017) for an Integrated Plasma Gasification Combined Cycle (IPGCC) to study the effect of varying oxygen ratio and steam ratio in plasma gas. The study suggested that at higher steam ratio resulted in increased hydrogen content in syngas, while higher oxygen ratio lead to lower syngas yield caused by formation of H2O and CO2. Similar plasma gasification model using Gibbs free energy equilibrium approach was used to simulate different industrial waste such as shredded tires, plywood with different gasifying agent, air and steam. Electrical efficiency from the gas products was studied by an IPGCC. Steam addition contributed to the increase in hydrogen yield(Valmundsson and Janajreh, 2011). However, there is a limitation in amount of steam as cooling effect may take place thus reducing efficiency. A model called EquipPlasmaJet (EPJ) model as shown in Figure 2 was developed for estimation of syngas production of a plasma gasification
process(Minutillo et al., 2009), which is part of an Integrated Plasma Gasification/Fuel Cell system was developed to predict the electrical efficiency. The EPJ model determined the composition of gas by minimizing Gibbs free energy. Electrical efficiency of fuel cell obtained was about 33% which higher than conventional incineration technology at about 20% (Galeno et al., 2011). The EPJ model was also used for another integrated system with a Combined Cycle system. Different blending of different wastes was investigated together with combination of different gasifying agents such as air, oxygen and steam for a plasma gasification process. It was discovered that a blend of equal amount of MSW and hazardous waste could achieve a plant efficiency of 24.3% by using pure air as plasma gas (Mazzoni et al., 2017).
Figure 2. Plasma gasification model of EPJ Model (Minutillo et al., 2009).
Kinetic based models were studied considering more detailed aspects of the process. There are some built in function within ASPEN for input of kinetic parameters. Kinetics can also be included via customized FORTRAN subroutines codes to represent desired model. A comparison between Gibbs energy minimization model and kinetic model was done by (Eikeland et al., 2015) to investigate the composition difference in the syngas composition.
Reaction rates to simulate actual reactions in the gasifier were defined in the kinetic model.
Consideration of rate of formation and residence time are factors that will affect the result in a kinetic model. Both models showed different outcomes from varying factors such as steam flow rate, reaction temperature and residence time. Results can vary because of the kinetics considered as seen in another model where a fluidized bed reactor for biomass gasification was simulated taking into account tar formation and cracking by including tar kinetics into the model allowing variation in feedstock and gasifying agent such as oxygen and steam. After comparing the model with experimental data, it was concluded that model performance can be enhanced by considering tar formation and kinetics (Kaushal and Tyagi, 2017). Comparably, a fluidized bed reactor used for biomass gasification process was also simulated that factored in reaction kinetics and hydrodynamic parameters representing fluidized reactions at the same time considering kinetics of char gasification. Validation of model was done against a lab scale experimental data. Both gasification temperature and steam-to-biomass ratio contributed to a higher production of hydrogen. ER was found to be optimum at 0.23, of which higher than that would decrease the carbon conversion efficiency(Nikoo and Mahinpey, 2008).
A semi detailed kinetic model was used to simulate a biomass gasification of wood in a bubbling fluidized bed. Empirical correlations and reaction kinetics of pyrolysis, hydrodynamics parameters were applied to obtain more accurate results while also considering tar formation in the model because it is one of the crucial part to commercialize gasification(Beheshti et al., 2015). Study showed thermal cracking of tar is better at increasing ER. Gasification temperature increase led to an increase in yield of H2 and CO because endothermic reactions are favorable at higher temperature. Steam addition also contributed to higher hydrogen yield.
Another model on fluidized bed gasification of wood was simulated by incorporating external Fortran code into Aspen Plus blocks to customize the model. Reaction kinetics and hydrodynamic parameters were considered in the model to better represent reactions in the fluidized bed gasifier. The model then was used to examine effects of different parameters such as air-fuel ratio, steam-fuel ratio and gasifier temperature. Increase amount of air not
only reduces yield of combustible fraction, H2 and CO but also introduced more N2 which decreases the overall calorific value of syngas. Steam-fuel ratio increase helped in producing more H2 and CO facilitated by more steam reforming reactions. Carbon conversion improved by increasing gasifier temperature shown in temperature range 600 – 1000 °C (Begum et al., 2013).
Break down of different reaction zones in a gasification process allows more in depth reactions to be considered although the zones may overlap in an actual process. (Pauls et al., 2016) developed a model for a gasification of woody biomass in a bubbling fluidized bed taking into account hydrodynamics, gasification kinetics, extensive pyrolysis reactions, and tar formation kinetics. A more realistic approach considering more empirical correlations for pyrolysis and char gasification resulted in more accurate results compared to original model by (Nikoo and Mahinpey, 2008) in terms of H2 and CO composition. However, CO2 and CH4 composition prediction were less accurate due their small composition. Detailed model of wood gasification was developed by breaking down into reaction zones for drying, pyrolysis, secondary reactions and char gasification by incorporating Fortran sub-models into existing model while at the same time considering more compounds in the reactions. The model also included syngas cleaning system for removal of inorganics and particles, and water treatment.
Results obtained was the syngas composed of major compounds 21% H2 and 42% CO, with calorific value 12.5 MJ/kg (Francois et al., 2013). Another detailed model of dual fluidized bed for biomass gasification by implementing chemical reactions for different reaction zones with external Fortran file to simulate operation of a fluidized bed reactor. The model also considered tar formation by grouping into 4 different groups of tar, namely benzene, phenol, naphthalene and toluene (Abdelouahed et al., 2012). It was concluded that prediction of CO, CO2 and H2 yield is dependent on the kinetic of the water-gas shift reaction, while result of methane and tar corresponds well with experimental data. Hence, as more details such as tar compounds and char gasification are considered, the prediction of the model can be more accurate.
2.3 Plasma Gasification
Studies using plasma gasification for treatment of feedstocks such as biomass and RDF have shown that a cleaner product can be produced for various applications. The high temperature from the plasma torch helps to promote tar cracking, converting light hydrocarbons into combustible gases. Presence of tar poses operational challenges such as erosion and corrosion in the gasifier. In order to achieve a cleaner syngas, a two stage fluidized bed which comprised of gasifier for primary gasification and a separate plasma reactor for tar cracking was designed to overcome some issues such as tar emission and ash slagging. A second stage reactor for plasma tar cracking showed that residual tars and char were able to be cracked as observed in the absence of organic carbon downstream of the plasma reactor as shown in Figure 3. Aromatic system can be destabilized at high temperature by thermal activation influences the tar conversion (Materazzi et al., 2014). Soot produced is also minimal with more effective tar decomposition. Furthermore, the syngas post plasma reactor was richer in H2 and CO than post gasifier as higher temperature enhances reactions such as water-gas shift reaction(Materazzi et al., 2016). Secondary oxygen as thermal cracking source was compared and it was found that plasma cracking can provide more independent control for tar cracking.
Figure 3. A two stage plasma gasification process (Materazzi et al., 2016).
A test reactor was used to assess plasma gasification of RDF consisted of paper, wood, plastic and organic material which were pelletized for feeding into the system. Plasma torch can prevent temperature fluctuations from the time dependent exothermic reactions by allowing independent control of heat input. Slag produced from the reactor was also tested and was determined to be suitable as secondary building materials according to Flemish legislation(Lemmens et al., 2007).
The Gasplasma process, a two-stage thermal treatment system for thermal conversion of waste developed by Advanced Plasma Power was simulated in ASPEN Plus for various waste materials such as landfill mined waste, MSW and industrial. Syngas exiting plasma converter showed negligible content of benzene which can be a good indicator for tar removal effectiveness. Calcia-alumina-silica rich slag as obtained from their gasification process went through leaching tests to investigate suitability as aggregate materials and it was found that pollutant levels were far below hazardous limit (Ray et al., 2012).
Plasma gasification is seen to have the potential to treat solid waste because of ability to drastically reduce waste volume and harmful impurities thus is being used for various solid waste from different sources. Syngas produced from plasma gasification of solid waste for high purity H2 productions in a H2 recovery system. Dioxins level measurements well below regulatory standards of Korea, USA and EU indicated that plasma treatment was able to decompose organics contained in waste. Carbon conversion efficiency of 97% was achieved suggesting that plasma treatment can be efficient in treatment of waste(Byun et al., 2011).
DC plasma torch with H2O/Ar was used for plasma gasification of biomass and waste resulted in syngas with high content of H2 and CO and negligible tar content. Sufficient residence time and optimum temperature in the reactor lead to low CO2 concentration despite CO2 being used as oxidizing agent (Hlina et al., 2014). Plasma gasification application was also investigated on treatment of solid waste from United States Air Force Basic Expeditionary Airfield Resources Base in a small reactor where major products obtained are H2 and CO(Vaidyanathan et al., 2007) . Mixture of MSW and raw wood are pre-treated using steam
mechanical heat treatment(SMHT) were used a feedstock for a plasma gasification reactor.
The SMHT turned MSW into refused derived biomass, and mixture with raw wood resulted in a compost-like form which is more suitable for gasification(Shie et al., 2014) . Study showed that increase in temperature and addition of steam contributed to the increase of H2 yield which subsequently increased the energy yield of syngas.
2.4 Tar Cracking
Besides the main product gases such as CO and H2, gasification also results in tars which could jeopardize the process by problems such as erosion and corrosion on turbines and engines thus making syngas that is produced from a gasification process undesirable for direct usage.
C10H8 and C7H8 were chosen to represent tar compounds in a study to model the thermal removal of tars at high temperature using plasma torch. Tar cracking model is as shown in Figure 4. The mathematical model was based on a CSTR model that considered different kinetics of tar cracking process. Comparison between equilibrium model that is based on Gibbs energy minimization method and kinetic model showed that tar conversion was near completion for both cases. Sensitivity analysis on influence of incoming temperature from gasifier showed that increase in gas temperature from gasifier would increase the temperature of gas exiting tar reactor. Tar composition can affect the composition of syngas, and it was shown at different overall C10H8 content where at higher content led to a rise in CO and H2 composition. However, it also increases the soot content in the output gas (Fourcault et al., 2010).
Figure 4. Tar Cracking Model (Fourcault et al., 2010).
Another study on tar thermal cracking using a CSTR model also predicted similar outcome of tar conversion of C10H8 and C7H8 taking in account reaction kinetics. The study shown that increased in plasma torch power not only increased tar conversion but also increased the LHV of the syngas. Char particles considered in this model also contributed higher content of CO and H2. Over Firing Air addition also enhanced tar conversion but affects the temperature due to rise in oxidation, decrease in LHV and increase of soot content in syngas (Marias et al., 2016).
A two stage Fluidized Bed plasma gasification process was used to study tar evolution using RDF as feedstock. Comparison of tar content post-Fluidized Bed Gasifier and post-plasma tar reactor showed high conversion of tar, where in equilibrium model showed complete conversion while plasma thermal model showed between 95 – 99% conversion of different tar compounds (Materazzi et al., 2014). The system showed an effective method of gas cleaning, higher conversion of carbon and higher yield of CO and H2.
2.5 Melting
An investigation of fly ash melting from incineration of MSW using Differential Scanning Calorimeter and Differential Thermographic Analysis to determine the heat capacity and heat of melting for fly ash at the same time using a thermodynamic model to determine the theoretical required heat that is used for comparison. Melting of fly ash from MSW generally occurs above 1300°C. Due to the high content of Cao in the ash sample, the experimental heat of melting range from 1.4 – 1.8 MJ/kg (Li et al., 2007). It was also predicted that heat of melting using gasification is lower than incineration process as shown in Figure 5 can vary according to operating conditions such as calorific value of waste and temperature of gasifier.
Figure 5. Comparison of required heat for incineration and gasification (Li et al., 2007).
Another study was conducted on the influence of addition of biomass ash to MSW fly ash on the melting characteristics. Investigation showed melting of pure MSW took place above 1400°C but with addition of biomass ashes, the melting temperature reduced. The total energy required to melt ash is the sensible heat required to raise the temperature of ash to the melting temperature and the latent heat of fusion for ash to change phase from solid to liquid. The model developed to predict the melting heat projected the heat in the range from 1.65 – 2.65 MJ/kg (Alhadj-Mallah et al., 2015).
3. METHODOLOGY
3.1 Plasma Gasification Process
A plasma gasification comprised of a fixed bed updraft gasifier and a plasma tar reactor was developed by ScanArc Plasma Technologies AB in Hofors, Sweden used to treat solid waste is shown in Figure 6. Solid waste is fed from the top of the gasifier while preheated air or steam as gasifying agent is fed from the bottom side of the reactor. The product from gasifier which contains volatile gases, moisture and tar goes to a separate plasma tar reactor where a high temperature plasma is used for tar cracking. A clean syngas is product at the end which is suitable for various applications. Meanwhile, a simplified scheme of the model is shown in Figure 7, which will be used for development of the ASPEN Plus model.
Figure 6. Schematic of two stage plasma gasification model.
3.2 Plasma Gasification Model 3.2.1 Feedstock properties
The feedstock used for the purpose of this study is excavation waste from a landfill site located at Mont-Saint-Guibert, Belgium. The waste was processed by sorting, screening and milling that resulted in a powder-like fraction that consists of RDF and inert materials. The composition of the RDF is shown in Table 1 while the ultimate and proximate analyses are shown in Table 2.
Table 1. Material Composition of RDF
Component, wt%
Plastics 21.46
Wood 11.90
Paper and cardboard 2.38
Textiles and fibres 0.94
Combustible fraction 21.15
Metals 5.49
Inert (soil, glass, etc.) 36.69
Table 2. Ultimate and proximate analyses of RDF
Proximate Analysis, wt% Ultimate Analysis, wt% (db)
Moisture content (ar) 30.00 Carbon 39.94
Fixed Carbon (db) 11.60 Hydrogen 5.50
Volatile matter (db) 48.40 Nitrogen 1.50
Ash (db) 40.00 Oxygen 11.00
Chlorine 1.77
Sulphur 0.29
LHV of raw RDF (MJ/kg) 11.848
Table 3. Analyses of metal contents of RDF
Metals content (mg/kg)
Silica (Si) 160000 Lead (Pb) 441
Aluminium (Al) 17700 Boron (B) 13.1
Calcium(Ca) 29800 Cadmium (Cd) 5.24
Iron (Fe) 21600 Cobalt (Co) 9.68
Potassium (K) 4950 Copper (Cu) 187
Magnesium (Mg) 2470 Chromium (Cr) 124
Manganese (Mn) 271 Mercury (Hg) 1.53
Sodium (Na) 2910 Molybdenum (Mo) 3.04
Phosphorus (P) 831 Nickel (Ni) 28.8
Titanium (Ti) 2090 Vanadium (V) 27.2
Arsenic (As) 5.66 Zinc (Zn) 1200
Barium (Ba) 378
Figure 7. Simplified schematic of the plasma gasification model.
3.2.2 Drying
Landfill waste contains a significant amount of water. The function of drying sub-model is to reduce the moisture that is contained in the wet feedstock where the temperature is between 100 – 150°C. The process of moisture removal occurs by the exchanging heat with the syngas that is flowing upwards from the lower section of the gasifier. Heat is used to heat up, evaporate and superheat steam, and also to heat up the feedstock as shown in (3). The mass balance of the drying block is shown in equation (2)
𝑚+,,-./012 = 𝑚456+ 𝑚809./:;, (2)
𝑄 = 𝑚+,,-./012∙ 1 − 𝑋809./:;, ∙ 𝐶B∙ 𝑇0:/− 𝑇9D + 𝑚+,,-./012∙ 𝑋809./:;,∙ (ℎ./,G8,IJKL− ℎ./,G8,IMN) (3)
3.2.3 Pyrolysis
Pyrolysis also known as de-volatilization occurs by heating without presence of oxygen that leads to decomposition into two main components, namely volatile matter and char. Volatile matter considered as shown in (4) consists of mainly gases such as 𝐻Q, 𝐶𝑂, 𝐶𝑂Q, 𝐶𝐻S, tar (𝐶TU𝐻V, 𝐶W𝐻V, 𝐶X𝐻X), while char is primarily fixed carbon and ash, where composition can be obtained from proximate and ultimate analysis of landfill waste. Process of pyrolysis is sustained by heat flux from the gasification at the lower part of gasifier. The sub-model for pyrolysis can be written in a one-step global reaction (4).
𝑅𝐷𝐹 → 𝐺𝑎𝑠 (𝐻Q, 𝐶𝑂, 𝐶𝑂Q, 𝐶𝐻S, 𝐻𝐶𝑙, 𝐻Q𝑆) + 𝑇𝑎𝑟(𝐶TU𝐻V, 𝐶W𝐻V, 𝐶X𝐻X) + 𝐶ℎ𝑎𝑟 (4)
It is expected that the temperature of upper zone is high thus tar can exit the gasifier as vapor and enter the tar cracking reactor.
3.2.4 Char Combustion and Gasification
The process of drying and pyrolysis result in char as a product and char is being treated as fixed carbon and ash. Char will undergo gasification and partial combustion in the presence of air as gasifying agent to form 𝐶𝑂 and 𝐶𝑂Q. Partial combustion is required as gasification reactions being exothermic reactions will supply the required heat for drying, pyrolysis and melting process. Reactions considered in air gasification are shown in table 4. This process will apply the Gibbs free energy theory where phase and chemical equilibrium is assumed because of the high temperature from the char combustion. Change in Gibbs free energy defines if a reaction is spontaneous or otherwise. When trying to determine Gibbs free energy at a fixed temperature and pressure, it can be written as (5). In order to obtain equilibrium composition, Gibbs free energy has to be minimized and finally achieve (6).
𝑑𝐺.d./,8 = 𝑑𝐻.d./,8− 𝑇𝑑𝑆.d./,8 (5)
𝑑𝐺.d./,8 = 0 (6)
Table 4. Char combustion and gasification reactions considered.
Reactions Type
R1 𝐶 + 𝐶𝑂Q → 2𝐶𝑂 (Boudouard reaction) Endothermic R2 𝐶 + 𝑂Q → 𝐶𝑂Q (Combustion) Exothermic R3 𝐶 + 0.5𝑂Q → 𝐶𝑂 (Combustion) Exothermic
3.2.5 Melting
Ash produced from char gasification consists of inorganic components of the feedstock is melted by the heat from partial oxidation process. The high temperature obtained from combustion is sufficient to melt the ash into slag that flows out at the bottom of the gasifier.
Ash can be assumed to consists of 70% 𝑆𝑖𝑂Q, 13% 𝐶𝑎𝑂, 9% 𝐹𝑒Q𝑂k 8% 𝐴𝑙Q𝑂k, according to metal contents in Table 3. Heat capacity of ash can be calculated according to equation (7) (Zhang et al., 2013) and Latent heat of fusion of ash is also calculated in a similar manner based on values from (Font et al., 2017),(Li et al., 2007),(Patnaik, 2003).
𝑐B,G.n = D9pT𝑥9𝑐B,9 (7)
3.2.6 Plasma Tar Cracking
Tar in the fixed bed updraft gasifier is carried over from the gasifier to the plasma reactor along with the gases produced from pyrolysis and char gasification process. In the pyrolysis process at temperature range 200 – 500 °C, tar is produced and leaves upwards into cooler regions above while exchanging heat with the feedstock, thus conversion of tar into gases is low, thus high amount of tar is present in the gas (Valderrama Rios et al., 2018). In this model, 3 major compounds of tars which are naphthalene, toluene, and benzene are considered.
Naphthalene was selected since it is often found as main compound in tertiary tar from biomass and waste gasification and it is difficult to crack due to its structure as Polycyclic Aromatic Hydrocarbon. For benzene, it is commonly used to represent primary tar while
Toluene formed at high temperature has a stable aromatic structure found in tars(Marias et al., 2016). Due to very high temperature of plasma, it is assumed that reaction reaches equilibrium very fast. Products are obtained by minimizing Gibbs energy. Reactions considered in the tar cracking reactor are shown in Table 5 where model was also based on a fixed bed reactor.
Table 5. Reactions considered for tar cracking.
Reaction References
R4 𝐶TU𝐻V+ 4𝐻Q𝑂 → 4𝐶𝑂 + 5𝐻Q (Jess, 1996) R5 𝐶W𝐻V+ 𝐻Q→ 𝐶X𝐻X+ 𝐶𝐻S (Jess, 1996) R6 𝐶X𝐻X + 5𝐻Q𝑂 → 5𝐶𝑂 + 6𝐻Q+ 𝐶𝐻S (Virk et al., 1974) R7 𝐶𝐻S+ 𝐻Q𝑂 → 𝐶𝑂 + 3𝐻Q (Nozahic, 2008)
R8 𝐻Q+1
2𝑂Q→ 𝐻Q𝑂 (Turns, 1996)
R9 𝐶𝑂 +1
2𝑂Q→ 𝐶𝑂Q (Petersen and Werther, 2005)
R10 𝐶𝑂 + 𝐻Q𝑂 → 𝐶𝑂Q+ 𝐻Q (Petersen and Werther, 2005) R11 𝐶𝑂Q+ 𝐻Q→ 𝐶𝑂 + 𝐻Q𝑂 (Petersen and Werther, 2005) R12 𝐶𝐻S+ 2𝑂Q → 𝐶𝑂Q+ 2𝐻Q𝑂 (Petersen and Werther, 2005)
R13 𝐶𝐻S+1
2𝑂Q→ 𝐶𝑂 + 2𝐻Q (Turns, 1996) R14 𝐶X𝐻X +15
2 𝑂Q→ 6𝐶𝑂Q+ 4𝐻Q𝑂 (Turns, 1996)
R15 𝐶X𝐻X + 3𝑂Q→ 6𝐶𝑂 + 3𝐻Q (Petersen and Werther, 2005) R16 𝐶W𝐻V+ 9𝑂Q → 7𝐶𝑂Q+ 4𝐻Q𝑂 (Turns, 1996)
Figure 8. Flowsheet of plasma gasification process in Aspen Plus.
3.3 ASPEN Plus Model description
The complete ASPEN Plus model is shown in Figure 8, while description of blocks, streams used are shown in Table 6, Table 7, Table 8 respectively. The feedstock properties, proximate and ultimate analyses was assigned to non-conventional stream ‘RDFF’ is fed into the model and first meets the gas mixture from the lower part of gasifier and increase in temperature of stream ‘RDFF2’ by exchanging heat in block ‘HEATEX1’ with stream ‘GASMIX1’ before moving to the block ‘DRYING’ where feedstock is converted into dry basis according to moisture content and then the stream ‘WETRDF’ is separated in the block ‘’SEPARATE’. The dry stream ‘DRYRDF’ is then broken down into elementary components in the block ‘PYRO’
according to a calculator based on the ultimate analysis. The stream ‘DECOMPRO’ which contains ash is separated into ‘ASH’ and stream ‘DECOMPRO2’, where block ‘PYRO2’
simulates de-volatilization process into volatile gases along with char and tar estimated based on reference from (Zaini et al., 2018) and (Di Blasi, 2004).
Heat streams for drying ‘Q-DRYING’, decomposition ‘Q-DECOMP’, pyrolysis ‘Q-PYRO’ and char gasification ‘Q-CHAR’ are connected between blocks to contain the enthalpy within the system as source of heat for each process are dependent on the char combustion and gasification process. The streams ‘ASH’ and ‘CHAR’ separated from the block ‘SEPARAT’ goes into the Gibbs block ‘CHARGAS’ for char combustion and gasification process with gasifying agent ‘AIR1’ of which its mass flow rate is calculated based on a specific ER that is within the range of typical gasification process and able to supply sufficient heat for drying, pyrolysis, and melting while taking into account the heat loss from the gasifier stream ‘Q-LOSS’.
Product of char combustion and gasification ‘CHARPRO’ containing ash is separated in block
‘SEPARAT2’ where stream ‘ASH2’ going to the ‘MELTING’ block. Product gases only stream
‘CHARPRO2’ moves up the gasifier and meet with stream ‘PYROCHAR’. An external heat stream is added to the block ‘MELTING’ because the melting heat required for melting ash into slag is calculated manually.
The stream ‘GASMIX2’ goes into the Gibbs block ‘TARCRACK’ for plasma tar cracking process with plasma air heated with heat input ‘ELECTRIC’ considering a heat loss stream ‘Q-LOSS3’
at the block ‘PLASTORC’ while ‘Q-LOSS2’ is the heat loss from the tar cracking reactor from the sensible heat of the output. The resulting product stream ‘HOTSYN’ proceeds for cooling process at block ‘AIREX’ where energy loss is recovered to preheat air for char gasification.
The output ‘HOTSYN2’ then goes to the block ‘H2OEX’ to heat up water into saturated steam if it is required. The final output of syngas stream is ‘COLDSYN’.
Table 6. Description of unit operation blocks in ASPEN Plus flowsheet.
ASPEN Plus Name Block ID Description
HeatX HEATEX1 Heat exchange between feedstock and gas mixture from lower part of gasifier
AIREX Heat exchange between air input and hot syngas
H20EX Heat exchange between water input and hot syngas
Heater PLASTORC Increases the temperature of the plasma air RStoic DRYING Converts feedstock into dry basis according to
moisture content
PYRO2 Breakdown volatile matter into volatile gases according to stoichiometry
MELTING Converts ash to slag
RYield PYRO Converts non-conventional stream ‘RDFF’ into conventional stream
RGibbs CHARGAS Simulates char gasification process by minimizing Gibbs free energy
TARCRACK Simulates tar cracking process by minimizing Gibbs free energy
Mixer MIX Combines gas mixture from char gasification and pyrolysis process
MIX1 Combines char and ash
MIX2 Combines moisture and gas mixture from lower part
of gasifier
SSplit SEPARAT Separates char from gases and tar
SEPARAT1 Separates ash from conventional stream
SEPARAT2 Separates ash from gases from char gasification Sep2 SEPARATE Separates moisture from feedstock
Table 7. Aspen Plus material streams.
ASPEN Plus Stream Stream ID Description
Material RDFF Feedstock flow RDF
RDFF2 Heat exchange of RDF with gas flow
WETRDF RDF moisture calculation using stoichiometry
DRYRDF Dry RDF without moisture
MOISTURE Moisture removed from RDF
DECOMPRO RDF decomposed into elements according to proximate and ultimate analysis
DECOPRO2 Ash is separated from decomposed RDF
ASH Separated ash from decomposition
PYROPRO Products form from pyrolysis according to stoichiometry based on experiment
PYROCHAR Mixture of gases from pyrolysis and char gasification
CHAR Char separated from gas mixture
CHAR2 Mixture of ash and char
CHARPRO Product from char gasification and combustion
CHARPRO2 Char gas product with ash separated
ASH2 Ash separated from char gases
SLAG Slag from melted ash
GAS+TAR Mixture of gases from pyrolysis and char gasification
GASMIX1 Mixture of gases and moisture
GASMIX2 Gas mixes heating incoming RDF
PLASAIR Heated carrier gas for plasma converter
AIR2 Carrier gas for plasma converter
COLDAIR Air input for char gasification and combustion
AIR1 Preheated air for char gasification and combustion
COLDH2O Water input for steam gasification when required
HOTSYN Product gas from tar cracking
HOTSYN2 Product gas after heat exchange for preheated air
COLDSYN Product gas after heat exchange with water
Table 8. Aspen Plus heat streams.
ASPEN Plus Stream Stream ID Description
Heat Q-DRYING Heat duty for moisture removal
Q-DECOMP Heat duty for decomposition of RDF
Q-PYRO Heat duty for pyrolysis
Q-CHAR Net heat duty from char gasification
Q-LOSS Heat loss from gasifier
ELECTRIC Electric power for plasma converter
Q-LOSS2 Heat loss from tar cracking reactor
Q-LOSS3 Heat loss from plasma converter
3.3.1 Assumptions
The following are assumptions used for the model:
• Steady state and the reactions reach chemical equilibrium.
• Syngas produced from pyrolysis consists of 𝐻Q, 𝐶𝑂, 𝐶𝑂Q, 𝐶𝐻S, 𝐻Q𝑆, 𝐻𝐶𝑙, tar (𝐶TU𝐻V, 𝐶W𝐻V) and char (as carbon and ash)
• 𝐴 𝐹./091 = 6.5 based on empirical formula using composition of C, H, O from ultimate analysis, 𝐶v𝐻V𝑂 + 6.5 𝑂Q+ 3.76𝑁Q → 5𝐶𝑂Q + 4𝐻Q𝑂 + 24.44𝑁Q
• Soot production is not considered.
• Ash is specified as non-conventional and non-reactive in the process.
3.3.2 Boundary Conditions
The operating conditions for the plasma gasification model is shown in Table 9.
Table 9. Boundary conditions for plasma gasification model.
RDF Feed (kg/hr) Flow rate (kg/hr) 1000
Pressure (bar) 1
Temperature (K) 298
Gasification Air, 𝑀yG.9 G9; Flow rate (kg/hr) 1325.88
Pressure (bar) 1
Temperature (K) 873
Equivalence Ratio 0.208
Gasifier Pressure (bar) 1
Temperature (K) 423 - 1773
Plasma Air, 𝑀BzG.8G G9; Flow rate (kg/hr) 406.89
Pressure (bar) 1
Temperature (K) 298
Plasma Torch Power (kW) 500
Heat Loss (%) Shaft Gasifier 5
Tar Cracking Reactor 5
Plasma Converter 30
3.4 Parameter Studies
Two different parameters were investigated using the ASPEN Plus model, namely air flow rate and preheated air temperature, which is shown in Table 10. Dimensionless number is used to better represent the studied parameter of air flow rate. Amount of actual air per kilogram of RDF compared to the stoichiometric amount can be represented as equivalence ratio(ER):
𝐸𝑅 = (||}~•M ~M€/‚ƒ„…
}~•M ~M€/‚ƒ„…)•LJM† (1)
Table 10. Parameters that were studied in the ASPEN Plus model.
Effect of ER Effect of Preheated
Air Temperature Gasification Air, 𝑀yG.9 G9; (kg/h) 1300 - 1950 1325.88
Plasma Air, 𝑀BzG.8G G9; (kg/h) 406.88 406.88 Preheated Air Temperature, 𝑇B;,n,G/ G9; (K) 873 373 - 1173
Plasma power, 𝑃BzG.8G (kW) 500 500
Dimensionless Parameters
ER 0.2 – 0.3 0.208
4. RESULTS AND DISCUSSION
4.1 Verification and Validation of Model
The model developed using Aspen Plus is validated and verified against a similar setup done by ScanArc Plasma Technologies AB. However, the feedstock is slightly different where it consists of mixture of wastes such as municipal waste, industrial waste, hazardous waste, car tyres, computer scrap which may result in different compositions of syngas. The comparison is shown in Table 11.
𝐿𝐻𝑉 = 𝐻𝐻𝑉 − 𝑀Š‹Œ∙ 𝐿Š‹Œ (8)
𝐻𝐻𝑉 =TU.W∙Š‹TUU•TQ.X∙ŽŒ (9)
𝐶𝐺𝐸 = •Š••‘N}~• ∙ |•‘N}~•
•Š•ƒ„… ∙ |ƒ„…•’zG.8G ’0“,; (10)
Table 11. Comparison of composition between Aspen Plus Model and Similar Setup
Model
(Mole %)
ScanArc Data (Mole %)
𝐶𝑂 18.2 20.9
𝐶𝑂Q 5.1 6.1
𝐻Q 18.9 15.9
𝐻Q𝑂 12.8 13.8
𝑁Q 44.6 43.1
LHV (MJ/Nm3) 4.66 4.34
CGE (%) 72.5 69.1
4.1.1 Syngas Composition Pre and Post Tar Cracking
Figure 9 shows the comparison between the gas composition before and after the tar cracking reactor. The figure showed that both H2 and CO2 increased from 16.96% to 18.90% and 3.57%
to 5.05% respectively while CO and H2O fell from 18.64% to 18.24% and 15.54% to 12.80%
correspondingly. Both CH4 and tar compounds are completely converted. The rise of H2 is attributed to the conversion of tar compounds according to (R4), (R6), (R7), (R15), (R16) from Table 5. This suggests that plasma tar cracking of light hydrocarbon such as tar compounds is beneficial should a syngas of higher H2 yield is desired besides cleaner syngas that can be utilised without much post treatment of syngas. By the same token, the decline in H2O could be related to the decomposition of tar compounds by moisture in the gas that exist as steam, thus contributing to the increment of H2 during tar cracking. This is consistent with the findings by (Materazzi et al., 2016). On the other hand, the drop in CO and rise in CO2 contradicts with the findings of (Materazzi et al., 2014). This could be associated by the (R10) where the activation energy is lower than (R11) according to (Fourcault et al., 2010) and the excess air that is supplied as plasma air.
Figure 9. Comparison between syngas composition before and after tar cracking.
0 5 10 15 20
H2 CO CO2 H2O CH4 TAR
Mole %
Pre-Tar Cracking Post-Tar Cracking
4.2 Mass and Energy Balance
A mass and energy balance for the plasma gasification model was done as shown in . while Table 12 shows the material balance for the system and Table 13 shows the energy balance of the system. Meanwhile, a Sankey diagram showing the flow of energy is illustrated in Figure 11 and the distribution of energy output is shown in Figure 12. The plasma power supplied as an input to the system was about 13% of the total energy input and the rest came from the RDF. The chemical energy of syngas comprised of 68.36%, the sensible heat was 24.30%, total heat loss including heat in slag was 7.34%. Thus, this gives the system a thermal efficiency of about 92%.
Figure 10. Mass and Energy Balance diagram for plasma gasification system.
Table 12. Mass balance of Aspen Plus model.
Input kg/h Output kg/h
RDF 1000 Syngas 2432.01
Gasification Air 1325.88 Slag 300.76
Plasma Air 406.89
Total 2732.77 Total 2732.77
Table 13. Energy balance of Aspen Plus model.
Input MJ/h Output MJ/h
RDF 11848.00 Syngas (Chemical Energy) 9329.94 Plasma Power 1800.00 Sensible Heat of Gas 3316.25
Slag 65.77
Heat Losses
Gasifier 225.25
Tar Cracking Reactor 170.79
Plasma Converter 540.00
Total 13648.00 Total 13648.00
Figure 11. Sankey diagram showing flow of energy for plasma gasification system.
Figure 12. Pie chart showing distribution of energy output.
4.3 Results of Parameter Studies 4.3.1 Effect of ER
As defined according to equation (1), ER is the ratio of actual air-fuel ratio against the stoichiometric air-fuel ratio for complete combustion. In this study, ER was varied from 0.2 – 0.3, where 𝑀yG.9 G9; is varied from 1300 – 1950 kg/h at a fixed 𝑇B;,n,G/ G9; at 873K. The influence of ER on the composition of syngas is shown in Figure 13 and on the LHV and CGE is shown in Figure 14. It can be observed that as ER increased, CO2 content rose while CO decreased. This occurred due to increased combustion reaction where CO2 was favoured.
Similarly, for reduction of H2 content where oxidation was favoured, thus increased the formation of H2O. The increase of overall N2 content was attributed by the increased in 𝑀yG.9 G9; and being inert. The drop in CO and H2, at the same time dilution of N2, caused the LHV of syngas and subsequently CGE to decline. The LHV ranged from 3.15 – 4.73 MJ/Nm3 while CGE ranged from 53.64 – 72.95%. Similar trends were shown by (Favas et al., 2017), (Begum et al., 2014), (Beheshti et al., 2015).
Figure 13. Effect of increasing ER on syngas composition at T”•–—–˜™ ˜š• = 873K
Figure 14. Effect of increasing ER on LHV and CGE.
0 0.1 0.2 0.3 0.4 0.5 0.6
0.200 0.220 0.240 0.260 0.280 0.300
Syngas composition (Mole Fraction)
ER
H2 CO CO2 N2 H2O
2 2.5 3 3.5 4 4.5 5
40%
50%
60%
70%
80%
0.200 0.220 0.240 0.260 0.280 0.300
LHV (MJ/Nm3)
CGE
ER
CGE LHV
4.3.2 Effect of Preheated Air Temperature
Preheating air helps in increasing efficiency of gasifier by reducing energy required from gasification. Thus, air input or ER can be reduced allowing lower amount of partial combustion which may lead to increasing amount of CO2. Reduction in ER helps retain the syngas calorific value within CO. The preheated air temperature used in the model is 873K, while air input is fixed at 1325.88 kg/h. Investigation on effect of 𝑇B;,n,G/ G9; on the model, the range of temperature from 373 – 1173K was studied at the specified flow rate for char gasification and combustion. Based on the boundary conditions fixed for the model, the heat of partial combustion required for all processes was determined and is plotted against the sensible heat from preheated air at the said range of temperature as shown in Figure 15. The graph shows that as 𝑇B;,n,G/ G9; increases, the portion of heat required from partial combustion of char decreases, thereby lowering ER for the process. As shown in Figure 16, the minimum ER at higher 𝑇B;,n,G/ G9; decreases. Hence, this translates to increasing LHV and CGE as shown in Figure 17 where it shows the minimum LHV and CGE for at each 𝑇B;,n,G/ G9; which is able to meet the heat demand of gasification. This phenomena is found to be similar with (Mathieu and Dubuisson, 2002) and (Doherty et al., 2009). LHV was found to be in the range of 3.96 – 5.03 MJ/Nm3 while CGE was in the range from 64.19 – 76.25%.
