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(2007) carried out the simulation calculation of char gasification of biomass py- rolysis products and the direct gasification of raw materials using ASPEN. PLUS.
Science of the Total Environment 628–629 (2018) 1278–1286

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Biomass gasification-gas turbine combustion for power generation system model based on ASPEN PLUS Weijuan Lan a,⁎, Guanyi Chen b,⁎, Xinli Zhu b, Xuetao Wang a, Chunmei Liu a, Bin Xu a a b

College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, PR China School of Environmental Science & Engineering, State Key Laboratory of Engines, Tianjin University, Tianjin 300350, PR China

H I G H L I G H T S

G R A P H I C A L

• An integrated system model was established based on ASPEN PLUS. • The flow of the integrated model for power generation from biomass gasification-gas turbine combustion was described. • A higher temperature is conducive to a higher syngas composition. • The simulated data are consistent with the experimental values. • The model can simulate the integrated system and obtain the main parameters of gas turbine.

An integrated model for power generation from biomass gasification-gas turbine combustion system.

a r t i c l e

a b s t r a c t

i n f o

Article history: Received 20 December 2017 Received in revised form 12 February 2018 Accepted 13 February 2018 Available online xxxx Keywords: Biomass gasification Gas turbine combustion Power generation ASPEN PLUS Model

⁎ Corresponding authors. E-mail address: [email protected] (W. Lan).

https://doi.org/10.1016/j.scitotenv.2018.02.159 0048-9697/© 2018 Elsevier B.V. All rights reserved.

A B S T R A C T

ASPEN PLUS is an important tool for process design. But in the biomass gasification-gas turbine combustion field, ASPEN PLUS has not been extensively studied. In this paper, the operation unit in the biomass gasification-gas turbine combustion power generation system was introduced. Based on ASPEN PLUS, an integrated system model for power generation by biomass gasification-gas turbine combustion was developed. The model consists of biomass gasification and gas-cleaning system, gas turbine combustion system, and power generation system. The main aim of this research was to develop an integrated power generation system model, to predict the gasifier performance and power generation under various operating conditions. Parameters such as temperature, equivalence ratio (ER), and catalyst affected the syngas composition and heating value. The results show that the simulated data are consistent with the experimental data. Considering M701F gas turbine as the research object, the process of integrated power generation system was described. The simulation of biomass gasification-gas turbine combustion integrated power generation system can simulate the integrated system and obtain the main parameters of gas turbine. The system model based on ASPEN PLUS can be used to predict power generation capacity from biomass gasification-gas turbine combustion system. © 2018 Elsevier B.V. All rights reserved.

W. Lan et al. / Science of the Total Environment 628–629 (2018) 1278–1286

1. Introduction Biomass energy has attracted more and more attention in the past decades (Chen et al., 2017). It can be preferable choice for the replacement of conventional fossil fuels in the near future. Gasification is a thermochemical process which converts carbonaceous materials into syngas (Laxmi et al., 2017). This is achieved by reacting the material at high temperature in an environment with oxygen and/or steam. Due to the low-oxidation conditions, gasification can be seen as a more environmentally friendly way of using biomass, as the pollutant emissions are lower (Jennifer et al., 2016). ASPEN PLUS is a problem-oriented input program used to facilitate the calculation of physical, chemical, and biological processes. It can be used to describe processes involving solids in addition to vapor and liquid streams (Puig et al., 2010). It is an important tool for process design. It is used to simulate coal conversion such as in the methanol synthesis process (Kundsen et al., 1982; Schwint, 1985), indirect coal liquefaction processes (Barker, 1983), integrated coal gasification combined cycle (IGCC) power plants (Phillips et al., 1986), and atmospheric fluidized-bed combustor processes (Douglas and Young, 1990). Researchers have developed models by using ASPEN PLUS to avoid complex processes and to develop the simplest possible model that can incorporate the main gasification reactions. In the field of biomass gasification, many researchers modeled the process of gasification by using ASPEN PLUS. For instance, Beheshti et al. (2015) developed a model to simulate air-steam gasification of biomass in a bubbling fluidised bed for hydrogen and syngas production. Mathieu and Dubuisson (2002) modeled wood gasification in a fluidized bed using ASPEN PLUS. The model was based on the minimization of Gibbs free energy, the flow of model was also described. The gasification processes were uncoupled to pyrolysis, combustion, Boudouard reaction, and gasification. The authors performed sensitivity analyses with respect to different parameters such as the oxygen factor, air temperature, oxygen content in air, operating pressure, and steam injection. Doherty and Reynolds (2013) developed a model in Aspen Plus for a fast internally circulating fluidized bed (FICFB) gasifier. Begum et al. (2013) developed an Aspen Plus model for an integrated fixed bed gasifier and predicted the steady-state performance of the model for different biomass feedstocks. Mansaray et al. (2002a, 2002b, 2002c) used ASPEN PLUS to simulate a dual-distributor-type fluidized-bed rice husk gasifier. The model was based on the homogeneous equilibrium theory, material and energy balances, and the two-phase theory of gas-solid fluidized beds. The three equilibrium reactions (water-gas shift, methanation, and oxidation) were used in the model. The model was kinetic-free and capable of predicting the reactor temperature and composition, higher heating value, and production rate of the produced gas. The fluidized bed was operated on wheat straw at various equivalence ratios (ERs), fluidization velocities, and bed heights. Both the predicted and experimental bed temperatures increased linearly with the increase in ER. Sensitivity of the kinetic-free homogeneous equilibrium model developed for the fluidized bed gasification of cereal straw was tested under a wide range of parameters, including ER, bed height, fluidization velocity, solid circulation coefficient, nitrogen–oxygen ratio, and fuel distribution function. The results show that the bed temperature was sensitive to changes in all these parameters. Mitta et al. (2006) modeled a fluidized-bed type gasification plant with air and steam using ASPEN PLUS, validated the results using a gasification pilot plant located at the Chemical Engineering Department of Technical University of Catalonia (UPC). Their gasification model was divided into three different stages: drying, devolatilization-pyrolysis, and gasification–combustion. Sreejith et al. (2013) developed an equilibrium model based on Gibbs free energy minimization for steam gasification of biomass using the Aspen Plus process simulator. They assumed that carbon is fully converted to product gases and no tar content is present in the gaseous product. Nikoo and Mahinpey (2008) developed a model capable of predicting the steady-state performance of an atmospheric fluidized-

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bed gasifier by considering the hydrodynamic and reaction kinetics simultaneously. They used four ASPEN PLUS reactor models and external FORTRAN subroutines for hydrodynamics and kinetics to simulate the gasification process. Im-orb et al. (2016) developed a model for a biomass gasification combined with a Fischer Tropsch process using Aspen plus to perform a techno-economic analysis of the integrated process with rice straw feedstock for green fuel They modeled oxygen supported gasification at 1000 °C, water gas shift at 150 °C to adjust H2/CO ratio to 2.37, and a slurry phase FT reactor at 220 °C and 20 bar. Chen et al. (2007) established a model of biomass gasification based on Gibbs free energy minimization. The authors performed a sensitivity analysis with ER and bed temperature, the results indicate that the gas composition was mostly affected by the bed temperature. The syngas heating value and gasification efficiency were mostly affected by the ER. The effects of air temperature on gas composition and gasification efficiency were also evaluated. They also found that the simulation values are consistent with the experimental data. Zhang et al. (2007) carried out the simulation calculation of char gasification of biomass pyrolysis products and the direct gasification of raw materials using ASPEN PLUS. The model was composed of RYIELD and RGIBBS units, and the gas phase reaction was assumed to be in the equilibrium state. The results show that the best working condition of the entrained flow gasification was the final pyrolys is temperature of 300 °C and O/C ratio between 0.9 and 1.1. The gasification temperature and conversion rate of carbon increased with increasing O/C molar ratio. For the semi-char at 300 °C, the air temperature was preheated to 550 °C. The gasification temperature reached up to 1056 °C, and the carbon conversion rate was close to 100%. Other researchers also modeled the gasification of coal and biomass using ASPEN PLUS. For example, Yan and Rudolph (2000) developed a model for a compartmented fluidized-bed coal gasifier process. Sudiro et al. (2009) modeled the gasification process to obtain synthetic natural gas from petcoke. Paviet et al. (2009) described a very simple twostep model of chemical equilibrium in a wood biomass gasification process. Robinson and Luyben (2008) developed an approximate gasifier model, this model can be used for dynamic analysis using ASPEN Dynamics. They used a high-molecular-weight hydrocarbon present in the ASPEN library as a pseudo fuel, and the proposed approximate model captured the essential macroscale thermal, flow, composition, and pressure dynamics. Doherty et al. (2008) and Doherty et al. (2009) developed a model for a circulating fluidized bed and studied the effect of diverse operating parameters including the ER, temperature, level of air preheating, biomass moisture, and steam injection on the product gas composition, gas heating value, and cold gas efficiency. Van der Meijden et al. (2009) also used ASPEN PLUS as a modeling tool to quantify the differences in overall process efficiency for producing synthetic natural gas in three different gasifiers (entrained-flow, allothermal, and circulating fluidized-bed gasifiers). However, in the biomass gasification-gas turbine combustion field, ASPEN PLUS has been less extensively studied. The main aim of this research was to develop an integrated power generation system model of a CFB biomass gasifier, and to predict the gasifier performance and power generation capacity under various operating conditions. Firstly, an integrated system model was developed in order to avoid complex processes. Secondly, the details of how operating conditions (such as temperature, ER and catalyst) effect on gasifier performance were evaluated. Thirdly in order to simulate the integrated system and obtain the main parameters of gas turbine, M701F gas turbine was taken as the research object, the process of integrated power generation system was described. 2. Model of biomass gasificatio-gas cleaning system It is necessary to prepare various basic data according to the requirements of software input conditions when ASPEN PLUS is used. The empirical method is very important to build a successful simulation

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Table 1 Reactor model (Ma, 2008). Model

Name

Description

Input Variables

RGIBBS RYIELD

Equilibrium reactor Yield reactor

Calculate based on the minimum free energy of GIBBS due to the limitation of atomic equilibrium Calculation the chemical reactor of the distribution ratio of known reaction products and unknown reaction kinetics model

Pressure, temperature Pressure, temperature

process. If a suitable gasification reaction model of biomass gasification process is established, the effects of different factors such as the gas yield, gas composition, and heating value on biomass gasification can be simulated and analyzed. 2.1. Assumption of biomass gasification system model In this paper, biomass gasification was performed in a fluidized gasifier. The reaction was close to balance at high temperatures. The Gibbs free energy minimization principle was applied to the gasification reaction. A biomass gasification model was established under certain assumptions as follows (Wang et al., 2004): ① The gasifier is in a stable state, all the parameters do not change with time. ② The material and agent were mixed completely and momentarily in the furnace. ③ The H, O, N, and S in the biomass were all converted into gasphase products, while the C did not change completely with the conditions. ④ There is no pressure decrease in the gasifier. ⑤ The ash in biomass is inert and is not involved in the gasification process. ⑥ The temperature of biomass particles is uniform and without gradient. ⑦ All the reactions are fast and reach to balance. 2.2. Biomass gasification system -gas cleaning system To develop a biomass gasification system-gas cleaning system, RYIELD and RGIBBS reactor modules were selected. The inputs of the gasification reactor module are shown in Table 1. The material flow in the process was as follows: Biomass gasification gas components such as CO, H2, CO2, CH4, N2, H2O, and O2 were defined as the routine components. BIOMASS and ASH were the nonconventional components. DECOMP module was simulated by yield reactor RYIELD. In this module, the biomass was decomposed into some

conventional solid elements, i.e., the product of gasification was the simplest form of each element such as O2, H2, S, C, N2, and ASH. Pyrolys heat (QDCOMP) was supplied as a part of the heat generated by the gasification module. The parameters needed for DECOMP pyrolysis module was to set the pyrolysis temperature to calculate the equilibrium. GASIFIER module simulated the biomass gasifier as well as its internal process. SSPLIT module after the GASIFIER module simulated the separation of gas and solid. The energy flow in this process was as follows: Some of the heat generated by the carbon combustion was the heat loss of the entire system, and some flowed to the pyrolysis reactor. The remaining heat was supplied to the gasification reaction to generate gas. In this study, the heat loss of the system was about 2% of the low heating value of biomass. In the pyrolysis module, the carbon conversion ratio was 99% in the gasifier using Fortran language. 2.3. Model description The simulation of biomass gasification - gas cleaning process was divided into two parts: Biomass gasification and gas cleaning. The gasification process was carried out as follow: The raw material BIOMASS was put into the DECOMP module after preheating to 300 °C to calculate the elemental yield. In this module, the biomass was decomposed into routine solid elements, i.e., the gasification product was the simplest form of each element such as O2, H2, S, C, N2, and ash. The product DECPROD entered the GASIFY reactor to calculate the gasification product according to the kinetic parameters, the product is raw gas with high temperature GAS1. The gas cleaning process was carried out as follows: The raw gas GAS1 was separated in the cyclone SPLIT(SSPLIT model) after coming out of the gasifier. The separated gas GAS2 was transferred to the condenser COOLING (HEATER model), achieving cooling and heat transfer. The products mixed with gas and tar (GLPROD) were passed through the gas–liquid separator SEP module, producing clean gas GAS3. Then, the clean gas GAS3 was transferred to the gas turbine combustor. Biomass gasification and gas cleaning process are shown in Fig. 1.

Fig. 1. The flow of biomass gasification - gas cleaning system.

W. Lan et al. / Science of the Total Environment 628–629 (2018) 1278–1286 BURN

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TURBINE

GAS3 FUEL

SPLIT

COMP

GEN

AIR3-3

AIR3-1 AIR2

AIR3

AIR3-2

EXHEATER

Fig. 2. Gas turbine system flow chart.

2.4. Physical property method The nonconventional solid component is a substance characterized by an empirical coefficient known as the component property. It is mixed with diverse solids. ASPEN PLUS can automatically handle such substances and simplifies when they are not involved in the calculation of chemical equilibrium and phase equilibrium (Wu et al., 2003). In this study, ASPEN PLUS was used to classify the components, process types, and reaction conditions to select the physical methods by providing the relevant information. The application of BK10, RK-SOAVE, and PR-BM of this model did not significantly affect the final result, because it is a general estimation method suitable for various temperature and pressure conditions. The physical properties of RKS-BM were selected based on the RK-Soave equation. This method is not only suitable for the mixture of nonpolar and weak polar components such as (hydrocarbons, CO2, and H2), but also suitable for biomass processing. Correct calculation results can be obtained even when the RKS-BM method is used in all the temperature and pressure ranges, it can also be used to simulate hydrocarbon refining and processing under high temperature and high pressure conditions. In this paper, the biomass gasification process was

carried out at a high temperature (1000 K) and atmospheric pressure. Therefore, it is reasonable to use the RKS-BM equation. 3. Model of gas turbine combustion system 3.1. Gas turbine combustion system module Higher quality gas is required for a gas turbine (H2S ≤ 200 mg/m3, tar and impurity b100 mg/m3) (Wu et al., 2003). For the integrated power system, COMPR module was used to simulate the compressor. TURBINE module was used to simulate the turbine. BURN module was used to simulate the combustion chamber. A reactor module (RGIBBS) simulation chamber was built based on ASPEN PLUS. Because the gas turbine system is also one of the major factors affecting the integrated system, the gas turbine power generation system should be simulated. 3.2. Process description M701F gas turbine was selected as the research object based on ASPEN PLUS. The process was carried out as follows: The air AIR2 was

Fig. 3. Flow chart of the integrated model for power generation from biomass gasification-gas turbine combustion system.

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fed into the compressor, compressed, and heated by the compressor COMP-AIR (COMPR module). Then, the air was defined as AIR3. The compressor exhaust was divided into two parts by assuming that all the cooling air was removed from the compressor outlet: About 83% of the air AIR3–1 was mixed with clean gas GAS3 and burned in the combustion chamber, then produced gas FUEL. About 17% of the air AIR3–2 was extracted from the compressor outlet, cooled, and pressurized through the cooler COOLING (EXHEATER unit). The cooling air AIR3–3 was mixed with the combustion chamber exhaust FUEL in the turbine inlet and fed into the TURBINE (COMPR module). Then, the gas turbine TURBWK (COMPR module) was operated. Finally, the gas was discharged from the gas turbine with cooling air after cooling and depressurization (Dong et al., 2005). The gas turbine module flow chart is shown in Fig. 2. 3.3. Physical model and transitivity method The physical methods used in the production of syngas in ASPEN PLUS are PR-BM (using the Peng Robinson equation of state with Boston–Mathias function) and RKS-BM (using the Redlich–Kwong– Soave equation of state with Boston-Matthias function). However, for a biomass gasification system, RKS-BM is more appropriate. In the process simulation, it is necessary to set up the tearing flow, convergence method, convergence module, and convergence order. These can be automatically determined by ASPEN PLUS and set by the user. To obtain a better convergence, the Broyden method was selected in this simulation. It is important that the initial estimate of the input tearing flow is one of the conditions for fast convergence. If not convergent, the number of iterations can be increased. 4. Model of power generation system At present, the main studies about the simulation of integrated systems are methanol and power system, dimethyl ether, and power system. Biomass gasification-gas turbine combustion has not been extensively studied. Thermodynamic simulation has been used in the process unit in the literature (Zhou et al., 2008; Benito et al., 2007). Because of the influence of reactor heat transfer, an actual industrial reaction system cannot reach thermodynamic equilibrium. There is a certain deviation between the simulated and actual data. At the same time, most of the current models consist of a single unit operation (Li et al., 2007; Ma et al., 2004), an integrated system model was not developed. It is difficult to determine the advantages and disadvantages of a system from macroscopic perspective. In this paper, an integrated system model for power generation by biomass gasification-gas turbine combustion was developed based on ASPEN PLUS. The process of biomass gasification-gas turbine combustion power generation system was as follows: a low-heating-value gas was produced, after removing impurities, it was condensed into clean gas. The clean gas was fed into the combustion chamber, thus driving the gas turbine to generate power.

Fig. 4. Effect of gasification temperature on syngas composition at ER = 0.15.

Based on ASPEN PLUS, the process of the integrated system can be described as follows: raw material BIOMASS was preheated to 300 °C and transferred to the DECOMP module to calculate the elemental yield. The biomass was decomposed into conventional solid elements, i.e., the gasification product was the simplest form of elements, for example, O2, H2, S, C, N2, and ash (ASH). The product DECPROD was transferred to the reactor GASIFY to calculate the gasification production according to the kinetic parameters. The product was raw gas with a high-temperature GAS1 raw gas. GAS1 was separated in the cyclone SPLIT(SSPLIT model) after coming out of the gasifier. The separated gas GAS2 was transferred to condenser COOLING (HEATER model), achieving cooling and heat transfer. The products mixed with gas and tar (GLPROD) were passed through the gas–liquid separator SEP module, and produced clean gas GAS3. Then, the clean gas was transferred to the gas turbine combustor. The air AIR2 was fed into the compressor, compressed, and heated using the compressor COMP-AIR (COMPR

Table 2 Biomass gasification simulation parameter settings. Item

Parameter settings

Environment temperature Heat exchanger Inlet parameters Gasifying agent Condenser

20 °C

Heat loss Gasification reactor Carbon conversion rate Ash

Inlet temperature of water: 20 °C Biomass flow: 1 kg/h; CaO/Biomass (w/w) = 0–30% Pressure: Constant pressure; temperature: 20 °C Inlet temperature: 650–900 °C; outlet temperature:150 °C 2LHV% (Gao et al., 2008) Pressure: constant pressure; temperature: 650–900 °C 98% Heat capacity 1.2 kJ/(kg·K)

Fig. 5. Effect of gasification temperature on syngas composition at ER = 0.20.

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Fig. 6. Effect of gasification temperature on syngas composition at ER = 0.25. Fig. 8. Effect of CaO/B on syngas composition.

module).The air was defined as AIR3. The compressor exhaust was divided into two parts by assuming that all the cooling air was removed from the compressor outlet: About 83% of the air AIR3–1 was mixed with clean gas GAS3 and burned in the combustion chamber, then produced gas FUEL. About 17% of the air AIR3–2 was extracted from the compressor outlet, cooled, and pressurized through the cooler COOLING (EXHEATER unit). The cooling air AIR3–3 was mixed with the combustion chamber exhaust FUEL in the turbine inlet and fed into the TURBINE (COMPR module). Then, the gas turbine TURBWK was operated. Finally, the gas was discharged from the gas turbine with cooling air after cooling and depressurization. The flow chart of the integrated system is shown in Fig. 3.

5. Simulation analysis of biomass gasification-gas cleaning system 5.1. Simulation results To investigate the accuracy of the model, the results of biomass gasification on fluidized bed were verified. The main input parameters and

conditions are shown in Table 2. The effects of operating conditions on biomass gasification performance were evaluated. 5.1.1. Effect of gasification temperature The model was validated against the experiments of Lan (2013) conducted on a pilot scale CFB gasifier. The experimental results were compared with the simulation results using the ASPEN PLUS model. The comparisons between the experimental and simulation results on syngas composition are shown in Figs. 4–6. H2, CO, CO2, and CH4 were the main components of gasification syngas. A higher temperature was found to be conducive to a higher volume fraction of combustible gas. A higher temperature slightly increases the yields of H2 and CH4. With the increase in temperature, the composition of CO increased significantly, decreasing the CO2 yield. The simulated data of CO and CO2 compositions are lower than the experimental results. However, the simulated data of CH4 and H2 compositions are higher than the experimental results. This can be explained as follows: In the chemical equilibrium, the composition of CnHm almost reaches 0% when the Gibbs free energy is minimized. Therefore, CnHm and other hydrocarbons are not considered in the simulation. According to the elemental balance of H and chemical equilibrium, the simulated data of CH4 and H2 compositions are higher than the experimental results. 5.1.2. Effect of ER The effect of ER on syngas composition was investigated. In this study, Fig. 7 shows the comparison of simulation and experimental results at a given temperature of 750 °C. Fig. 7 shows that the simulated data are consistent with the experimental values, and the basic trend is almost the same. With the increase in ER, the yields of H2, CO, and CH4 decreased. However, the yields of CO2 increased. The simulated data of CH4 and H2 are higher than the experimental results. However, CO and CO2 compositions obtained from the simulation are lower than the experimental results. This is because

Table 3 Proximate analysis, ultimate analysis, and high heating value (HHV) of wood flour.

Fig. 7. Effect of ER on syngas composition at 750 °C.

Proximate analysis (wtar%)

Ultimate analysis (wt%)

HHV (kJ/kg)

Ma 4.9

C 47

O 42.2

a

Va 77.3

FCa 17.7

Aa 0.4

H 6.9

N 3.4

S 0.1

M – moisture; V – volatile matters; FC – fixed carbon; A – ash.

19,070

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Table 4 Comparison of simulation and experimental results.

Table 6 The main calculation conditions of the system.

Syngas composition (%) and low heating value (kJ/kg)

Experimental results

Simulation results

H2 CO CO2 CH4 CnHm Low heating value

7.70 23.50 10.70 5.30 0.36 5930

7.85 23.05 9.93 6.72 0.00 5880

Reactor Parameters Gasifier Pressure: atmospheric pressure; temperature: 750 °C; carbon conversion rate: 98%; temperature of crude gas/clean gas at outlet heat exchanger: 150 °C GT Model: M701F; compression ratio: 17; inlet temperature: 1400 °C, cooling air rate: 17%; adiabatic efficiency of the gas turbine: 0.9; exhaust pressure: 0.1047 MPa

Table 7 The main simulation results of thermal parameters.

when the Gibbs free energy is minimized in the chemical equilibrium, the composition of CnHm almost became 0%. Therefore, in the simulation, CnHm and other hydrocarbons are ignored among the gaseous products. In addition, the simulation process follows the elemental balance of H and chemical equilibrium. The yields of CnHm and other hydrocarbons are equal to those of H2 and CH4 in the simulation. Therefore, the CH4 and H2 compositions obtained from the simulation are higher than the experimental results.

5.1.3. Effect of catalyst In this study, CaO was used as the catalyst in the simulation and experiments. The effect of catalyst on syngas composition was evaluated by changing the ratio of CaO/B. Fig. 8 shows the comparison of simulation with experimental results regarding the effect of CaO/B on syngas composition at a given temperature of 750 °C. Fig. 8 shows that the syngas compositions vary significantly with increasing CaO content from 0% to 20%. The increase in CaO content clearly increased the yield of H2, the composition of CO increased as well. The content of CO2 in syngas decreased with the increase in CaO content. However, the yield of CH4 slightly increased. Compared to the experimental results, the simulated data of CO2 was lower, and that of H2 was higher. This is probably because CaO reacted with CO2 and was completely consumed. However, ASPEN PLUS simulation software ignores the loss of CaO. Therefore, the CO2 composition obtained from simulation is lower than the experimental result, and H2 composition is higher. Therefore, the consumption of CaO should be considered in the simulation if the conditions permit. Furthermore, the simulation results show that the addition of CaO slightly affected the compositions of CH4 and CO, consistent with the experimental results.

AIR2 AIR3–1 AIR3–2 GAS3 FUEL EXH AIR4 (Cooling)

Temperature (°C)

Pressure (bar)

Vapor (Frac)

Enthalpy MMkal/h

20 400.5726 400.5726 338 1400.6452 597.400 20

1.01325 17.32658 17.32658 1.01325 17.32658 1.10895 15.0647

1 1 1 1 1 1 1

−5.0312 160.7655 36.6841 −26.0023 49.9782 −412.0078 −1.4968

5.2.1. Simulation results of wood flour gasification Table 4 shows that the simulated data are consistent with the experimental results. The model ignores the CnHm, and the simulation process follows the elemental balance of H. Therefore, the compositions of H2 and CH4 obtained from the simulation are higher than the experimental results. The results indicate that the model has a universal applicability. 5.3. Simulation analysis of gas turbine combustion system 5.3.1. Selection of relative parameters of gas turbine combustion system In the gas turbine system, the parameters input into the ASPEN PLUS simulation software can be divided into three types: (1) flow rate, temperature, pressure, and components of system inlet air AIR2 and fuel GAS3, (2) input pressure ratio and isentropic efficiency of compressor and turbine module, (3) exhaust pressure and heat loss LOSSHEAT of combustion chamber module (Dong et al., 2005). The parameters required in the thermodynamic calculation model are listed in Table 5. In addition, the gas turbines work under standard conditions, in which the atmospheric parameters are as follows: The temperature is 15 °C, and the pressure is 101,325 Pa. The relative humidity is 60% (Ma, 2008). The M701F gas turbine produced by Mitsubishi was selected as the object in this study.

5.2. Model sensitivity analysis To verify the universality of the model, the operation data (Wu et al., 2003) of Sanya wood flour gasification power plant in Hainan were selected and analyzed. The proximate and ultimate analyses are shown in Table 3. Table 4 shows the comparison of the simulation and experimental results (Chen et al., 2007) of syngas composition and low heating value at 750 °C.

Table 5 Design parameters of M701F gas turbine. Parameters

Design value

Compressor pressure ratio Turbine pressure ratio Net power (MW) Inlet temperature of gas turbine (°C) Outlet temperature of gas turbine (°C) Air flow rate (kg/s) Net efficiency (%) Isentropic efficiency of gas turbine Heat balance calculation temperature (°C)

17 17 270 1400 586 651 38.2 0.900 1245

5.4. Simulation results and analysis of integrated power generation system from biomass gasification-gas turbine combustion 5.4.1. Simulation of system The clean gas simulated using the gasification–purification system described in Section 5.1 was used in this simulation. The main calculation conditions of the system are shown in Table 6. On the ASPEN PLUS software platform, Fortran language program was used to simulate the entire power generation system. Tables 7 and 8 show the simulation and calculation results. 5.4.2. Simulation results The results show that the temperatures of the gas turbine and smoke emission are consistent with the operating regulations. The net powers of the system calculated in the simulation are listed in Table 9. Table 8 The main simulation results of work flow. Unit

COMPWK

TURBWK

Network

Power MW

265.32803

−535.82241

−270.49438

W. Lan et al. / Science of the Total Environment 628–629 (2018) 1278–1286 Table 9 The main simulation results of operating parameters. Parameters

Design value

Compressor pressure ratio Turbine pressure ratio Net power (MW) Inlet temperature of gas turbine (°C) Outlet temperature of gas turbine (°C) Power consumption rate of compressor Isentropic efficiency of compressor Isentropic efficiency of gas turbine Combustion efficiency of combustor Heat balance calculation temperature (°C)

17.033 16.816 270.494 1480.6452 597.400 0.1187 0.895 0.900 0.991 1238.000

Table 9 shows that the net power and inlet temperature of gas turbine are 270.494 MW and 1480.6 °C, respectively. The simulations are close to the set value. Thus, the calculation method for gas turbine model is relatively reliable. 6. Conclusions In this paper, an integrated system model was developed in order to avoid complex processes. The process of integrated power generation system was described. The details of how operating conditions (such as temperature, ER and catalyst) effect on gasifier performance were evaluated. M701F gas turbine was taken as the research object in order to simulate the integrated system and obtain the main parameters of gas turbine. The system model based on ASPEN PLUS can be used to predict power generation capacity from biomass gasification-gas turbine combustion system. (1) To investigate the accuracy of the model, the results of biomass gasification on fluidized bed were verified. A higher temperature is conducive to a higher syngas composition. A higher temperature slightly increased the yields of H2 and CH4. With the increase in temperature, the composition of CO increased significantly while decreasing the CO2 yield. The simulated data of CO and CO2 compositions are lower than the experimental results. (2) With the increase in ER, the yields of H2, CO, and CH4 increased. However, a higher ER decreased the CO2 composition. The simulated data of CH4 and H2 are higher than the experimental results. However, CO and CO2 compositions obtained from the simulation are lower than the experimental results. (3) An increase in CaO content clearly increased the yield of H2, as well as the composition of CO. The CO2 content in syngas decreased with the increase in CaO content. However, the yield of CH4 increased slightly. (4) Considering M701F gas turbine as the research object, the process of integrated power generation system was described. The simulation of biomass gasification-gas turbine combustion integrated power generation system can simulate the integrated system and obtain the main parameters of gas turbine. Acknowledgements This work was supported by the Natural Science Foundation of Henan Province (No. 162300410014), Henan University of Science and Technology PhD startup fund Projects (No. 09001759), the National Natural Science Foundation of China (No. 51506046). References Barker, R.E., 1983. ASPEN Modeling of the Tri-state Indirect-liquefaction process. Oak Ridge National Laboratory, Oak Ridge, USA. Begum, S., Rasul, M., Akbar, D., Ramzan, N., 2013. Performance analysis of an integrated fixed bed gasifier model for different biomass feedstocks. Energies. 12, 6508–6524.

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