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Research Papers: Energy Systems Analysis

# A Comparative Study of Syngas Production From Two Types of Biomass Feedstocks With Waste Heat RecoveryPUBLIC ACCESS

[+] Author and Article Information
Shahid Islam

Faculty of Engineering and Applied Science,
University of Ontario Institute of Technology,
2000 Simcoe Street North,
Mechanical Engineering Department,
King Fahd University of Petroleum and Minerals,
Dhahran 31261, Saudi Arabia
e-mail: shahid.islam@uoit.ca

Ibrahim Dincer

Faculty of Engineering and Applied Science,
University of Ontario Institute of Technology,
2000 Simcoe Street North,
Mechanical Engineering Faculty,
Yildiz Technical University,
Besiktas, Istanbul, Turkey

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received October 27, 2017; final manuscript received March 25, 2018; published online April 19, 2018. Editor: Hameed Metghalchi.

J. Energy Resour. Technol 140(9), 092002 (Apr 19, 2018) (11 pages) Paper No: JERT-17-1597; doi: 10.1115/1.4039873 History: Received October 27, 2017; Revised March 25, 2018

## Abstract

This paper deals with an integrated biomass system developed for syngas production with waste heat recovery option and analyzes this system thermodynamically using both energy and exergy approaches. Also, an aspenplus simulation model is developed to demonstrate comparative gasification analyses of wood (Birch) and olive waste using Gibbs reactor for syngas production. Gibbs free energy minimization technique is applied to calculate the equilibrium of chemical reactions. In this newly developed model, the heat of the product syngas and the waste heat from the flue gas are recovered through a unique integration of four heat exchangers to produce steam for the gasification process. The sensitivity analyses are performed to observe the variations in the concentration of the methane, carbon monoxide and carbon dioxide in syngas against various operating conditions. Furthermore, the performance of gasifier is indicated through cold gas energy efficiency (CGE) and cold gas exergy efficiency (CGEX). The overall energy and exergy analyses are also conducted, and the comparisons reveal that the biomass composed of olive waste yields high magnitude of overall and cold gas energy efficiencies, whereas wood (Birch) yields high magnitude of overall and cold gas exergy efficiencies. Moreover, the energy of the product syngas is recovered through an expander which enhances energy and exergy efficiencies of the overall system. The present results show that the CGE, CGEX, and overall energetic and exergetic efficiencies follow a decreasing trend with the increase in combustion temperature. The proposed system has superior and unique features as compared to conventional biomass gasification systems.

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## Introduction

The demand of energy is increasing worldwide due to growing population and higher living standards. The combustion of fossil fuels, mainly coal, natural gas and petroleum, supply most of the energy demand of the world. The utilization of fossil fuels through combustion to meet the increasing energy demand results in fast depletion of fossil fuel reserves and environmental degradation like acid rain, smog formation, global warming, ozone depletion, and health hazards.

The energy conservation and search for alternative source of energy is crucial to encounter with energy crisis and environmental pollution. In past, various investigations have been done on the conservation of energy in fossil fueled power generation systems. It is important to exploit alternative sources of energy effectively to mitigate environmental concerns and global warming. In 2012 and 2013, the contribution of renewable for energy consumption and electricity generation was 19% and 22%, respectively [1].

The natural sources of energy like sunlight, wind, geothermal, biomass, rain, and tides are treated as renewable energy resources, which are replenished naturally after use. Thermochemical conversion processes like pyrolysis and gasification are very attractive to convert biomass into syngas. Biomass is a biological material which is largely extracted from living or dead matter available on the earth [2]. Numerous researchers have studied biomass energy-based cogeneration systems for numerous industries like palm oil, rice, wood, sugar, and paper [3]. Assima et al. [4] employed three low cost materials including iron, bone meal, and ashes as catalysts for the gasification of urban waste. Landis et al. [5] developed a decision support system to help stakeholders to make decisions about tradeoffs and synergies against alternative landscape composition, configuration, and agronomic management. Martyniak et al. [6] conducted an experimental study of few wild populations of a new bioenergy grass species to determine traits related to biomass quality and quantity.

The pyrolysis is a decomposition process of biomass at high temperature without air and the resulting volatiles include water, nitrogen (N2), carbon dioxide (CO2), oxygen (O2), hydrogen (H2), methane (CH4), hydrogen disulfide (H2S), and carbon monoxide (CO) [7]. In addition to this, a small amount of unsaturated hydrocarbons includes olefins, acetylene, aromatic, and char [8]. Steam, air, oxygen, and carbon dioxide are commonly used as gasification agents for the conversion of char into gases. The fluidized bed reactors are more frequently used for gasification as compared to the other kinds of reactors because of the high rate of heat and mass transfer which ultimately yields high production of gas. The use of steam as gasification agent is one of the auspicious option for biomass conversion [9,10]. Thapa and Halvorsen concluded that the contribution of the factors like devolatilization, water–gas shift reactions, and gasification in the presence of steam is more dominating than others in the product gas heating value [11].

Currently, the use of coal is almost sovereign for electricity generation and has become controversial due to the concerns about global climate change as its huge contribution to high production of carbon dioxide [12]. Renewable energy sources excluding hydropower are continually offering more potential than the actual energy production. The energy conservation techniques and the energy efficiency calculations have exhibited compelling results over past three decades. In addition to this, energy efficient processes predict to offset some of the dependency on oil imports and compensate increased electric power demand to some extent [12].

The lower heating value (LHV) of the produced gas is influenced by the type of oxidizing agent. The selection of air as an oxidizing agent results in a low calorific value gas. Oxygen or steam as oxidizer leads to a medium calorific value gas. The latter one is more appropriate as a gasifying agent for synthesis of liquid fuels and chemicals, whereas the former one is more suitable when the heat contents are not critical [10].

The gasifiers can be divided into three main categories which include entrained flow, fluidized bed, and moving/fixed bed. Downdraft gasifiers are highly efficient for the biomass gasification but these are feasible for small scale, whereas syngas with high tar contents is produced through updraft gasifier. Fluidized bed gasifiers are highly flexible in terms of fuel and scale; therefore, these are appropriate selection for biomass gasification. Cohce et al. [2] performed energy and exergy analysis of a hydrogen production system based on biomass and evaluated overall performance of the system along with cold gas efficiency of the gasifier.

Kumar et al. [13] simulated the performance of a lab‐scale gasifier and predicted the flow rate and composition of product from given biomass composition and gasifier operating conditions using the aspenplus software. They applied mass balance, energy balance, and minimization of Gibbs free energy during the gasification to determine the product gas composition and validated the model through a lab-scale fluidized bed gasifier using corn stover and distillers grains as the feed materials. Kumar et al. [14] developed and optimized an aspenplus-based model to convert biomass into power, fuels, and chemicals through thermochemical gasification. Moreover, they maximized the net energy efficiency for biomass gasification and estimated the cost of producing industrial gas.

Zhang et al. [15] compared the pyrolysis behavior of several selected biomass samples, namely, pine wood, poplar wood, wheat straw, and sugarcane bagasse, with a particular attention to the effect of lignin. Jin et al. [16] performed supercritical water gasification of biomass due to the unique chemical and physical properties and reported that it is an efficient and clean conversion. Ren et al. [17] investigated the emissions of hydrogen chloride (HCl) gas from combustion of biomass composed of raw or terrified corn straw in a fixed bed, as a function of the mass flow rate of the air through the bed and the moisture content of the fuel. Wladyslaw [18] presented the results of combustion process of two-phase charge contained coal and wetted biomass, where the carrier was the air with given flow rate. Chen et al. [19] reported practical significance of improving the application of coal-bed gas engine technology through hydrogen addition which improves operation stability and enlarges lean burn limit of coal-bed gas engine. The cyclone gasification technology is commonly used for biomass fuels with small particle sizes, such as rice husks and wood chips [20]. The production of inexpensive, environmentally benign biodiesel is possible through catalytic conversion of waste palm oil [21]. Kordoghli et al. [22] optimized the gas fraction produced as a result of catalyzed pyrolysis of scrap tires in order to identify the influence of catalysts on gas composition during the main thermal range of the decomposition process.

The specific objectives of this research are to develop a gasification model which can generate the required quantity of steam through waste heat and recovers the energy of the produced gas through expander. In addition to this, the performance of two types of feedstock (wood Birch and olive waste) is compared including cold gas energy efficiency (CGE), cold gas exergy, and energy and exergy efficiencies of overall system. Moreover, a parametric investigation is conducted for both the feedstocks to determine the sensitivities of energy and exergy efficiencies of overall system against variations in operating conditions.

## Model Description

The newly developed model uses two types of feedstocks wood (Birch) and olive waste. The description of equipment and stream codes used in the simulation is tabulated in Tables 1 and 2, respectively. Moreover, reaction equations for the gasification are tabulated in Table 3. The stream of biomass is fed to the splitter in the simulation model. The chemical composition of the feedstock used in aspenplus model is taken from Zanzi et al. [23] and tabulated in Table 4. Feed is introduced in a splitter which supplies 75% to the mixer and 25% to the combustion reactor. The hot air at 450 °C enters the combustion reactor where combustion reaction is set to generate heat for the gasifier (Gibbs reactor).

The combustion temperature is set at 55 °C above the temperature of the gases entering the reactor [24]. The heat stream Q-GIBBS generated as a result of combustion is supplied to Gibbs reactor for gasification. The steam at 470 °C is mixed with the feed in mixer and supplied to Gibbs reactor. The main parameters entered in simulation model are presented in Table 5. Thermochemical conversion of the feedstock is done in this reactor in the presence of gasifying agent steam, under Gibbs minimization energy approach. The chemical reaction equations presented in Table 3 are entered in this reactor. The produced syngas is directed to the separator which separates waste water from the gases. Then, this high pressure syngas is passed through an expander which recovers and heat of this gas is transferred to the ambient water flowing across the heat exchanger 1 (HEX 1). The water enters HEX 1 at 25 °C and leaves at 102 °C, then this steam is passed through HEX 2 where it absorbs more heat from the waste and its temperature is raised to 330 °C.

The heat of the flue gases is recovered at two stages first in HEX 3 which heats up the ambient air and this ambient air is supplied to the combustion reactor. Then, the flue gases are passed through the heat exchanger 4 which heats up the steam to the required gasification temperature of 470 °C. Finally, the heat of this flue gas is used for the drying purpose of the biomass before gasification.

The LHV, higher heating value (HHV) enthalpy, and density of the produced syngas are specified with HCOALGEN and DCOALGEN property models present in aspenplus [25]. The Peng–Robinson property method with Boston–Mathias modification is selected for this study. The exiting stream “COLDSYN” represents the final syngas produced through gasification.

## Analysis and Assessment

The aspenplus is selected to develop and perform sensitivity analysis of the syngas produced from two types of biomass feedstocks. The following lists the assumptions made to investigate performance and sensitivity of the proposed system. The equilibrium assumption followed in this study is that no rapid shift occurs when different species exist in a mixture (e.g., see Ref. [26]):

• The temperature T0 = 25 °C and the pressure P0 = 1 bar are taken as dead state properties of the multigeneration system.

• The operating conditions and all flow processes of the system are of steady-state.

• All reactors and separators are adiabatic.

• The tar production is negligible, and the char is composed of solid carbon.

• Negligible or no changes in the kinetic and/or potential energies.

• Air is mainly composed of 79% N2 and 21% O2.

• The ideal gas properties are chosen for air to perform analysis.

• The isentropic efficiency of 85% is taken for expander.

• The selected property method is Peng–Robinson (PR) equation of state with Boston–Mathias (BM) modification (PR–BM) being used [2].

• The LHV and the HHV for wood (Birch) and olive waste are 31.84 MJ/kg and 26.03 MJ/kg, and 17.07 MJ/kg and 19.67 MJ/kg, respectively [23].

The balance equations related to mass, energy, exergy, and entropy of the proposed systems are presented here. Moreover, energetic and exergetic performances of subsystems and multigeneration system with irreversibility rate are also discussed.

aspenplus calculates mass and energy magnitudes for all streams, however, mass and energy balances for a general process in steady-state can be written as Display Formula

(1)$∑im˙i=∑em˙o$
Display Formula
(2)$∑iE˙in=∑eE˙out$

The overall exergy balance for steady-state process can be expressed as Display Formula

(3)$∑Ex˙iin=∑Ex˙iout+∑Ex˙dest$

where $∑Ex˙iin$ represents the sum of rate of exergy destruction at inlet. The exergy destruction rate of biomass and steam mixture can be written as Display Formula

(4)$∑Ex˙iin=Ex˙air+Ex˙drybio+Ex˙biomoist+Ex˙st$

and the sum of rate of exergy destruction at exit $∑Ex˙iout$ can be calculated as Display Formula

(5)$∑Ex˙iout=Ex˙prodg+Ex˙flueg+Ex˙WH2O+Ex˙st+W˙net$

The combustion reactor and gasifier both account physical and chemical exergies at inlet and exit states. Chemical exergies are the exergies associated with combustion process and chemical reactions, whereas only physical exergies are related to heat exchangers as there is no chemical change or reactions. The sum of specific physical and specific chemical exergy is the total specific exergy flow at any specified state which can be found as Display Formula

(6)$ex=exph+exch$

The specific physical exergy can be written as Display Formula

(7)$exph=h−h0−T0(s−s0)$

The gas mixture is assumed to be ideal for the calculations of the specific chemical exergies so the equation can be defined as Display Formula

(8)$exch=∑ixi(exich−RT0lnxi)$

where $xi$ and $exich$ represent the mole fraction and the chemical exergy (standard) associated with component “i,” respectively. The values of standard chemical exergies are based on model 2 developed by Szargut et al. [27].

The entropy balance related to the steady flow system can be calculated as Display Formula

(9)$∑jQ˙jTj+∑im˙isi−∑em˙ese+S˙gen=0$
The exergy destruction occurring as a result of irreversibilities can be defined as Display Formula
(10)$Ex˙dest=T0S˙gen$

Biomass enters the yield reactor at ambient conditions hence the physical exergy is taken as zero. Szargut [28] developed a statistical correlation factor to calculate chemical exergy of solid biofuels which is used in this study to find the correlation factor for wood (Birch) and olive waste Display Formula

(11)$β=1044+0.0160HC−0.34930C[1+0.0531HC]+0.0493NC(1044+OC)$

The above equation is based on no sulfur contents as the amount of sulfur is very small in biomass. So, the specific chemical exergies of the selected feedstocks can be found as Display Formula

(12)$Exch,drybio=βLHVbio$

The specific heat at constant pressure of the biomass is calculated as [29] Display Formula

(13)$Cp,bio=1.5+10−3T$

where $Cp,bio$ is the heat capacity and T is the temperature (K) of the biomass.

The change in the specific entropy corresponding to the temperature can be expressed as Display Formula

(14)$ΔS=∫T0TCpTdT$

The CGE is a mean to figure out the performance of the gasifier which can be calculated as Display Formula

(15)$ηcg=m˙prodgLHVprodgm˙drybioLHVdrybio$

The energy efficiency of any component at state I can be written as Display Formula

(16)$ηi=1−E˙outiE˙ini$

The energetic efficiency of the overall system can be expressed as Display Formula

(17)$ηsys=m˙prodgLHVprodg+Q˙WH2O,net+Q˙Flueg,net+W˙netm˙drybioLHVdrybio$

The cold gas exergy efficiency (CGEX) of the gasifier can be found as Display Formula

(18)$ψcg=m˙prodgHHVprodgm˙drybioHHVdrybio$

The exergy efficiency of any component at state I can be written as Display Formula

(19)$ψi=1−E˙xdestiE˙ini$
The exergy efficiency of the overall system can be expressed as Display Formula
(20)$ψsys=m˙prodgHHVprodg+Q˙WH2O,net1−T0Ts+Q˙Flueg,net1−T0Ts+W˙netm˙drybioHHVdrybio$

The ratio of steam to biomass can be calculated as Display Formula

(21)$STBR=m˙stm˙drybio$

## Results and Discussion

This section includes detailed performance analysis of a syngas production system based on two types of biomass feedstock. The dead state properties of pressure and temperature for exergy analysis are assumed as P0 = 1 bar and T0 = 25 °C, respectively. Thermodynamic model is developed to investigate the performance of the developed system. Then, an aspenplus simulation model is developed and sensitivity analysis is performed to compare the performance of wood (Birch)-based and olive waste-based systems as presented in Fig. 1. The results obtained through the simulations are verified through energy and exergy analyses of the thermodynamic model and compared with typical biomass-based system available in the literature. The model configuration, operating pressure and temperature for both feedstocks are kept same for the comparison. The performance of both models is assessed against variation in several design parameters. Simulation of each component is done with the help of a numerical solver called Aspen (Plus). The thermodynamic analyses of both models are performed with respect to the working fluid properties and reference to stream labels as presented in Fig. 1.

The syngas composition on the basis of percentage volume fraction, CGE, CGEX, and energy and exergy efficiencies of both feedstocks are presented in Fig. 2. It can be seen that the use of wood (Birch) yields more volume fraction of hydrogen and carbon monoxide, whereas the yield of methane and carbon dioxide is more in the case of olive waste. In addition to this, CGE and overall energy efficiencies of the wood (Birch)-based system and olive waste-based system are found to be 38% and 46.5%, and 36% and 45%, respectively. It is important to note that both CGE and overall energy efficiencies of the wood (Birch)-based system are more as compared to the olive waste-based system. This is because of the reason that these values are based on the lower heating values of feedstock and syngas produced, and the LHV of wood is much higher than the LHV of the olive waste, whereas there is no significant difference between the LHVs of the syngas produced by the systems running on two different feedstocks. It is also important to note that overall energy efficiencies of both feedstock are not much lower than the CGEs; this is due to the fact that the waste heat of the water coming out of the gasifier and the flue gases are used to produce required amount of steam and to heat up the required amount of air.

The CGEX and the overall exergy efficiency for the wood (Birch) and olive waste-based feedstocks are found to be 71% and 62%, and 74% and 65%, respectively. It can be noted that the exergy efficiencies follow the opposite trend. This is due the fact that the HHV of the wood (Birch) is less as compared to the HHV of the olive waste. The influences of operating modes and conditions on volume fraction based yield of the syngas, CGE, CGEX, and overall energy and exergy efficiencies of both feeds are discussed as below.

###### Effect of Mass Flow Rate of Steam on Syngas Composition.

The effect of fluctuation of mass flow rate of steam in the gasifiers of wood (Birch)-based model and olive waste-based model on the volume fraction based composition of the syngas is illustrated in Figs. 3 and 4, respectively. The yield of methane and carbon monoxide in both models decreases when the mass flow rate of steam is increased up to 50 kg/h, whereas the yield of carbon dioxide and hydrogen is enhanced with the increase in mass flow rate of steam. This trend is because of the reason that homogeneous reaction 5 in Table 3 is much favored with the increase in the mass flow rate of steam as compared to the other reactions.

###### Effect of Gasifier Pressure on Syngas Composition.

The effect of variation in the pressure of gasifiers of wood (Birch)-based model and olive waste-based model on the volume fraction based composition of the syngas is illustrated in Figs. 5 and 6, respectively. The pressure of the gasifier is varied from 1 bar to 8 bar to observe its effects on the composition of the syngas. The yield of methane and carbon monoxide and carbon dioxide in both models is increased with the increase in the pressure of the gasifier. Conversely, the yield of hydrogen in both models decreases with the increment in the pressure. It is significant to note that the trend of decrease in the yield of hydrogen is more in wood (Birch)-based system as compared to the olive waste-based system.

###### Effect of Combustion Temperature on Syngas Composition.

The temperature in the combustion reactor is varied from 500 °C to 1500 °C to investigate its effects on the composition of the syngas as shown in Figs. 7 and 8, respectively. The yield of methane and carbon dioxide in both models is enhanced with the rise in the temperature of combustion reactor, whereas the yield of carbon monoxide and hydrogen decreases with the increase in the combustion reactor. This is because of the reason that heat of the combustion reactor is the driving factor of the gasifier and the temperature of the gasifier increases with the increase in the combustion temperature which in turn favors the heterogeneous reaction 1 in Table 3 as compared to the other reactions. On the other hand, the yield of hydrogen and carbon monoxide decreases with the increase in combustion temperature which means forward homogeneous reaction 4 in Table 3 is more favorable at low temperature.

###### Effect of Combustion Reactor Temperature on Lower Heating Value, Higher Heating Value, Cold Gas Energy Efficiency, and Cold Gas Exergy Efficiency.

The sensitivity of low heating values, high heating value, cold gas efficiency, and cold gas exergy efficiency is observed against the combustion temperature range between 900 °C and 1200 °C as depicted in Figs. 9 and 10, respectively. It can be noted that LHV increases with the increase in the combustion temperature, whereas HHV decreases up to 1140 °C, then it increases sharply up to 1200 °C for wood (Birch)-based system. Both LHV and HHV for olive waste-based system are enhanced with the rise in the combustion temperature. Moreover, cold gas energy efficiency as well as exergy efficiency of the wood (Birch)-based and olive waste-based systems is decreased from 37.8% and 74% to 37.2% and 72.8%, and 46.5% and 64.5% to 45.9% and 63.5%, respectively. This trend is found to be almost same for both feedstocks with a slight variation.

###### Effect of Combustion Temperature on Overall Efficiencies.

The sensitivity of the overall energy and exergy trend/behavior of the wood (Birch)-based and olive waste-based systems is observed against the variation in the combustion temperature between 900 °C and 1200 °C as depicted in Figs. 11 and 12, respectively. The overall energy and exergy efficiencies of wood (Birch)-based and olive waste-based systems are decreased from 35.8% and 70.1% to 35.2% and 69.8%, and 44.5% and 61.5% to 43.9% and 60.5%, respectively.

## Conclusions

The precise energy, exergy, and thermal analyses are conducted for two types of biomass feedstocks. The operating conditions are varied to analyze the effects on the composition of syngas and overall system efficiencies. The integration of renewable energy resource and comprehensive energy and exergy investigations yield imperative results. The overall and cold gas energy efficiencies of the olive waste-based system are found to be higher as compared to wood (Birch)-based system. Conversely, the overall and cold gas exergy efficiencies of wood (Birch)-based system are found to be higher than olive waste-based system. The integration of energy recovery expander enhances the overall energy and exergy efficiencies of the system. The parametric study shows that the LHV and HHV of the syngas produced through both feedstocks are enhanced with the increase in the combustion temperature, whereas overall energetic and exergetic efficiencies of both developed models follow a decreasing trend with the increase in the combustion temperature. Furthermore, some of the significant conclusive remarks are summarized as follows:

• The energy recovered through expander and unique waste heat recovery with the help of four heat exchangers yields high magnitude of energy and exergy efficiencies associated with overall system.

• The cold gas energy efficiencies of wood (Birch)- and olive waste-based systems are found to be 37.8% and 46.5%, respectively.

• The cold gas exergy efficiencies of wood (Birch)- and olive waste-based systems are in the order of 74% and 64.5%, respectively.

• The LHV and the HHV of wood (Birch)-based system are found to be 12,026 kJ/kg and 13,628 kJ/kg, respectively.

• The LHV and the HHV of olive waste-based system are found to be 12,033 kJ/kg and 13,614 kJ/kg, respectively.

• The overall energy efficiencies of wood (Birch)- and olive waste-based systems with and without expander are found to be 35.8% and 44.5%, and 34.9% and 43.5%, respectively.

• The overall exergy efficiencies of wood (Birch)- and olive waste-based systems with and without expander are found to be 71% and 61.5%, and 70.2% and 60.6%, respectively.

## Acknowledgements

The authors sincerely acknowledge the aspenplus modeling support provided by Dr. Umer Zahid, Assistant Professor at Department of Chemical Engineering, KFUPM in Saudi Arabia.

## Nomenclature

• c =

compressor

• $E˙x$ =

exergy rate (kW)

• ex =

specific exergy (kJ/kg)

• h =

specific enthalpy (kJ/kg)

• LHV =

lower heating value (kJ/kg)

• $m˙$ =

mass flow rate (kg/h)

• P =

pressure (bar)

• $Q˙$ =

heat rate (kW)

• s =

specific entropy (kJ/kg K)

• $S˙gen$ =

rate of entropy generation (kW/K)

• T =

temperature (°C)

• vol =

volume

• $W˙$ =

work rate (kW)

Greek Symbols
• Delta =

change

• $η$ =

energy efficiency

• ρ =

density (kg/$m3$)

• $ψ$ =

exergy efficiency

• $∅$ =

fuel ratio (exergy to energy)

Subscripts
• a =

absorber

• bio =

biomass

• biomoist =

moisture in the biomass

• cg =

cold gas

• ch =

chemical

• dest =

destruction

• drybio =

dry biomass

• flueg =

flue gases

• HEX =

heat exchanger

• P =

pump

• ph =

physical

• prod =

product

• prodg =

product gas

• st =

steam

• WH2O =

waste water

• 0 =

environment state/(reference)

Acronyms
• CGE =

cold gas efficiency

• CGEX =

cold gas exergy efficiency

• HEX =

heat exchanger

• maf =

moisture and ash free

## References

Sawin, J. L. , 2014, “ Renewables 2014 Global Status Report,” REN 21 Secretariat, Paris, France, accessed May 7, 2015,
Cohce, M. K. , Dincer, I. , and Rosen, M. A. , 2011, “ Energy and Exergy Analyses of a Biomass-Based Hydrogen Production System,” Bioresour. Technol., 102(18), pp. 8466–8474. [PubMed]
Mujeebu, M. A. , Jayaraj, S. , Ashok, S. , Abdullah, M. Z. , and Khalil, M. , 2009, “ Feasibility Study of Cogeneration in a Plywood Industry With Power Export to Grid,” Appl. Energy, 86(5), pp. 657–662.
Assima, S. , Dell'Orco, G. P. , Navaee-Ardeh, J.-M. , and Lavoie, S. , 2017, “ Catalytic Conversion of Residual Fine Char Recovered by Aqueous Scrubbing of Syngas From Urban Biomass Gasification,” Biomass Bioenergy, 100, pp. 98–107.
Landis, D. A. , Gratton, C. , Jackson, R. D. , Gross, K. L. , Duncan, D. S. , Liang, C. , Meehan, T. D. , Robertson, B. A. , Schmidt, T. M. , Stahlheber, K. A. , Tiedje, J. M. , and Werling, B. P. , 2017, “ Biomass and Biofuel Crop Effects on Biodiversity and Ecosystem Services in the North Central US,” Biomass Bioenergy, in press.
Martyniak, D. , Żurek, G. , and Prokopiuk, K. , 2017, “ Biomass Yield and Quality of Wild Populations of Tall Wheatgrass [Elymus Elongatus (Host.) Runemark],” Biomass Bioenergy, 101, pp. 21–29.
Lapa, N. , Santos Oliveira, J. F. , Camacho, S. L. , and Circeo, L. J. , 2002, “ An Ecotoxic Risk Assessment of Residue Materials Produced by the Plasma Pyrolysis/Vitrification (PP/V) Process,” Waste Manage., 22(3), pp. 335–342.
Basu, P. , 2013, Biomass Gasification, Pyrolysis and Torrefaction, Practical Design and Theory, 2nd ed., Academic Press, San Diego, CA.
Wilk, V. , Kitzler, H. , Koppatz, S. , Pfeifer, C. , and Hofbauer, H. , 2010, “ Gasification of Residues and Waste Wood in a Dual Fluidised Bed Steam Gasifier,” International Conference on Polygeneration Strategies (ICPS 10), Leipzig, Germany, Sept. 7–9, p. 10.
Hofbauer, H. , Rauch, R. , Bosch, K. , Koch, R. , and Aichernig, C. , 2002, “ Biomass CHP Plant Güssing—A Success Story,” Expert Meeting on Pyrolysis and Gasification of Biomass and Waste, Strasbourg, France, Sept. 30–Oct. 1, p. 13.
Thapa, R. K. , and Halvorsen, B. M. , 2014, “ Stepwise Analysis of Reactions and Reacting Flow in a Dual Fluidized Bed Gasification Reactor,” Adv. Fluid Mech., 82(12), pp. 37–48.
Ratner, M. , and Glover, C. , 2014, “ U.S. energy: Overview and Key Statistics,” Congressional Research Service, p. 40.
Kumar, A. , Noureddini, H. , Demirel, Y. , Jones, D. D. , and Hanna, M. A. , 2009, “ Simulation of Corn Stover and Distillers Grains Gasificaion With Aspen plus,” Am. Soc. Agric. Biol. Eng., 52(6), pp. 1989–1995.
Kumar, A. , Demirel, Y. , Jones, D. D. , and Hanna, M. A. , 2010, “ Optimization and Economic Evaluation of Industrial Gas Production and Combined Heat and Power Generation From Gasification of Corn Stover and Distillers Grains,” Bioresour. Technol., 101(10), pp. 3696–3701. [PubMed]
Zhang, Z. , Zhu, M. , Hobson, P. , Doherty, W. , and Zhang, D. , 2018, “ Contrasting the Pyrolysis Behavior of Selected Biomass and the Effect of Lignin,” ASME J. Energy Resour. Technol., 140(6), p. 062201.
Jin, H. , Chen, B. , Zhao, X. , and Cao, C. , 2017, “ Molecular Dynamic Simulation of Hydrogen Production by Catalytic Gasification of Key Intermediates of Biomass in Supercritical Water,” ASME J. Energy Resour. Technol., 140(4), p. 041801.
Ren, X. , Meng, X. , Panahi, A. , Rokni, E. , Sun, R. , and Levendis, A. Y. , 2017, “ Hydrogen Chloride Release From Combustion of Corn Straw in a Fixed Bed,” ASME J. Energy Resour. Technol., 140(5), p. 051801.
Wladyslaw, M. , 2017, “ Co-Combustion of Pulverized Coal and Biomass in Fluidized Bed of Furnace,” ASME J. Energy Resour. Technol., 139(6), p. 062204.
Chen, L. , Song, P. , Long, W. , Feng, L. , Zhang, J. , and Wang, Y. , 2017, “ Experimental Study of Operation Stability of a Spark Ignition Engine Fueled With Coal Bed Gas,” ASME J. Energy Resour. Technol., 139(4), p. 044501.
Zhao, Y. , Feng, D. , Zhang, Z. , Sun, S. , Che, H. , and Luan, J. , 2017, “ Experimental Study on Autothermal Cyclone Air Gasification of Biomass,” ASME J. Energy Resour. Technol., 140(4), p. 042001.
Thushari, P. G. I. , and Babel, S. , 2017, “ Biodiesel Production From Waste Palm Oil Using Palm Empty Fruit Bunch-Derived Novel Carbon Acid Catalyst,” ASME J. Energy Resour. Technol., 140(3), p. 032204.
Kordoghli, S. , Paraschiv, M. , Tazerout, M. , Khiari, B. , and Zagrouba, F. , 2016, “ Novel Catalytic Systems for Waste Tires Pyrolysis: Optimization of Gas Fraction,” ASME J. Energy Resour. Technol., 139(3), p. 032203.
Zanzi, R. , Sjöström, K. , and Björnbom, E. , 2002, “ Rapid Pyrolysis of Agricultural Residues at High Temperature,” Biomass Bioenergy, 23(5), pp. 357–366.
Pröll, T. , Rauch, R. , Aichernig, C. , and Hofbauer, H. , 2007, “ Fluidized Bed Steam Gasification of Solid Biomass—Performance Characteristics of an 8 MWth Combined Heat and Power Plant,” Int. J. Chem. React. Eng., 5(1), pp. 937–944.
Doherty, W. , Reynolds, A. , and Kennedy, D. , 2013, Materials and Processes for Energy: Communicating Current Research and Technological Developments, A. Méndez-Vilas , ed., Formatex Research Centre, Badajoz, Spain.
Keating, E. L. , 2007, Applied Combustion, 2nd ed., Taylor & Francis, New York.
Szargut, J. , Morris, D. R. , and Steward, F. R. , 1988, Exergy Analysis of Thermal, Chemical, and Metallurgical Process, Hemisphere Publishing Corporation, New York.
Szargut, J. , 2005, Exergy Method: Technical and Ecological Applications, WIT Press, Boston, MA.
Gronli, M. G. , Melaaen, M. C. , Grønli, M. , and Melaaen, M. C. , 2000, “ Mathematical Model for Wood Pyrolysis—Comparison of Experimental Measurements With Model Predictions,” Energy Fuels, 14(4), pp. 791–800.
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## References

Sawin, J. L. , 2014, “ Renewables 2014 Global Status Report,” REN 21 Secretariat, Paris, France, accessed May 7, 2015,
Cohce, M. K. , Dincer, I. , and Rosen, M. A. , 2011, “ Energy and Exergy Analyses of a Biomass-Based Hydrogen Production System,” Bioresour. Technol., 102(18), pp. 8466–8474. [PubMed]
Mujeebu, M. A. , Jayaraj, S. , Ashok, S. , Abdullah, M. Z. , and Khalil, M. , 2009, “ Feasibility Study of Cogeneration in a Plywood Industry With Power Export to Grid,” Appl. Energy, 86(5), pp. 657–662.
Assima, S. , Dell'Orco, G. P. , Navaee-Ardeh, J.-M. , and Lavoie, S. , 2017, “ Catalytic Conversion of Residual Fine Char Recovered by Aqueous Scrubbing of Syngas From Urban Biomass Gasification,” Biomass Bioenergy, 100, pp. 98–107.
Landis, D. A. , Gratton, C. , Jackson, R. D. , Gross, K. L. , Duncan, D. S. , Liang, C. , Meehan, T. D. , Robertson, B. A. , Schmidt, T. M. , Stahlheber, K. A. , Tiedje, J. M. , and Werling, B. P. , 2017, “ Biomass and Biofuel Crop Effects on Biodiversity and Ecosystem Services in the North Central US,” Biomass Bioenergy, in press.
Martyniak, D. , Żurek, G. , and Prokopiuk, K. , 2017, “ Biomass Yield and Quality of Wild Populations of Tall Wheatgrass [Elymus Elongatus (Host.) Runemark],” Biomass Bioenergy, 101, pp. 21–29.
Lapa, N. , Santos Oliveira, J. F. , Camacho, S. L. , and Circeo, L. J. , 2002, “ An Ecotoxic Risk Assessment of Residue Materials Produced by the Plasma Pyrolysis/Vitrification (PP/V) Process,” Waste Manage., 22(3), pp. 335–342.
Basu, P. , 2013, Biomass Gasification, Pyrolysis and Torrefaction, Practical Design and Theory, 2nd ed., Academic Press, San Diego, CA.
Wilk, V. , Kitzler, H. , Koppatz, S. , Pfeifer, C. , and Hofbauer, H. , 2010, “ Gasification of Residues and Waste Wood in a Dual Fluidised Bed Steam Gasifier,” International Conference on Polygeneration Strategies (ICPS 10), Leipzig, Germany, Sept. 7–9, p. 10.
Hofbauer, H. , Rauch, R. , Bosch, K. , Koch, R. , and Aichernig, C. , 2002, “ Biomass CHP Plant Güssing—A Success Story,” Expert Meeting on Pyrolysis and Gasification of Biomass and Waste, Strasbourg, France, Sept. 30–Oct. 1, p. 13.
Thapa, R. K. , and Halvorsen, B. M. , 2014, “ Stepwise Analysis of Reactions and Reacting Flow in a Dual Fluidized Bed Gasification Reactor,” Adv. Fluid Mech., 82(12), pp. 37–48.
Ratner, M. , and Glover, C. , 2014, “ U.S. energy: Overview and Key Statistics,” Congressional Research Service, p. 40.
Kumar, A. , Noureddini, H. , Demirel, Y. , Jones, D. D. , and Hanna, M. A. , 2009, “ Simulation of Corn Stover and Distillers Grains Gasificaion With Aspen plus,” Am. Soc. Agric. Biol. Eng., 52(6), pp. 1989–1995.
Kumar, A. , Demirel, Y. , Jones, D. D. , and Hanna, M. A. , 2010, “ Optimization and Economic Evaluation of Industrial Gas Production and Combined Heat and Power Generation From Gasification of Corn Stover and Distillers Grains,” Bioresour. Technol., 101(10), pp. 3696–3701. [PubMed]
Zhang, Z. , Zhu, M. , Hobson, P. , Doherty, W. , and Zhang, D. , 2018, “ Contrasting the Pyrolysis Behavior of Selected Biomass and the Effect of Lignin,” ASME J. Energy Resour. Technol., 140(6), p. 062201.
Jin, H. , Chen, B. , Zhao, X. , and Cao, C. , 2017, “ Molecular Dynamic Simulation of Hydrogen Production by Catalytic Gasification of Key Intermediates of Biomass in Supercritical Water,” ASME J. Energy Resour. Technol., 140(4), p. 041801.
Ren, X. , Meng, X. , Panahi, A. , Rokni, E. , Sun, R. , and Levendis, A. Y. , 2017, “ Hydrogen Chloride Release From Combustion of Corn Straw in a Fixed Bed,” ASME J. Energy Resour. Technol., 140(5), p. 051801.
Wladyslaw, M. , 2017, “ Co-Combustion of Pulverized Coal and Biomass in Fluidized Bed of Furnace,” ASME J. Energy Resour. Technol., 139(6), p. 062204.
Chen, L. , Song, P. , Long, W. , Feng, L. , Zhang, J. , and Wang, Y. , 2017, “ Experimental Study of Operation Stability of a Spark Ignition Engine Fueled With Coal Bed Gas,” ASME J. Energy Resour. Technol., 139(4), p. 044501.
Zhao, Y. , Feng, D. , Zhang, Z. , Sun, S. , Che, H. , and Luan, J. , 2017, “ Experimental Study on Autothermal Cyclone Air Gasification of Biomass,” ASME J. Energy Resour. Technol., 140(4), p. 042001.
Thushari, P. G. I. , and Babel, S. , 2017, “ Biodiesel Production From Waste Palm Oil Using Palm Empty Fruit Bunch-Derived Novel Carbon Acid Catalyst,” ASME J. Energy Resour. Technol., 140(3), p. 032204.
Kordoghli, S. , Paraschiv, M. , Tazerout, M. , Khiari, B. , and Zagrouba, F. , 2016, “ Novel Catalytic Systems for Waste Tires Pyrolysis: Optimization of Gas Fraction,” ASME J. Energy Resour. Technol., 139(3), p. 032203.
Zanzi, R. , Sjöström, K. , and Björnbom, E. , 2002, “ Rapid Pyrolysis of Agricultural Residues at High Temperature,” Biomass Bioenergy, 23(5), pp. 357–366.
Pröll, T. , Rauch, R. , Aichernig, C. , and Hofbauer, H. , 2007, “ Fluidized Bed Steam Gasification of Solid Biomass—Performance Characteristics of an 8 MWth Combined Heat and Power Plant,” Int. J. Chem. React. Eng., 5(1), pp. 937–944.
Doherty, W. , Reynolds, A. , and Kennedy, D. , 2013, Materials and Processes for Energy: Communicating Current Research and Technological Developments, A. Méndez-Vilas , ed., Formatex Research Centre, Badajoz, Spain.
Keating, E. L. , 2007, Applied Combustion, 2nd ed., Taylor & Francis, New York.
Szargut, J. , Morris, D. R. , and Steward, F. R. , 1988, Exergy Analysis of Thermal, Chemical, and Metallurgical Process, Hemisphere Publishing Corporation, New York.
Szargut, J. , 2005, Exergy Method: Technical and Ecological Applications, WIT Press, Boston, MA.
Gronli, M. G. , Melaaen, M. C. , Grønli, M. , and Melaaen, M. C. , 2000, “ Mathematical Model for Wood Pyrolysis—Comparison of Experimental Measurements With Model Predictions,” Energy Fuels, 14(4), pp. 791–800.

## Figures

Fig. 1

aspenplus process flow sheet of biomass energy-based system for syngas production with waste heat recovery system

Fig. 2

Comparison of elemental yields of syngas (volume %, dry basis), and energy and exergy efficiencies of wood (Birch) and olive waste

Fig. 3

Effect of variation in the mass flow rate of steam on volume fraction (dry basis) of methane, carbon monoxide, carbon dioxide, and hydrogen using wood (Birch)

Fig. 4

Effect of variation in the mass flow rate of steam on volume fraction (dry basis) of methane, carbon monoxide, carbon dioxide, and hydrogen using olive waste

Fig. 5

Effect of variation in the gasifier pressure on volume fraction (dry basis) of methane, carbon monoxide, carbon dioxide, and hydrogen using wood (Birch)

Fig. 6

Effect of variation in the gasifier pressure on volume fraction (dry basis) of methane, carbon monoxide, carbon dioxide, and hydrogen using olive waste

Fig. 7

Effect of variation in the combustion temperature on volume fraction (dry basis) of methane, carbon monoxide, carbon dioxide, and hydrogen using wood (Birch)

Fig. 8

Effect of variation in the combustion temperature on volume fraction (dry basis) of methane, carbon monoxide, carbon dioxide, and hydrogen using olive waste

Fig. 9

Effect of variation in the combustion temperature on LHV, HHV, CGE, and CGEX using wood (Birch)

Fig. 10

Effect of variation in the combustion temperature on LHV, HHV, CGE, and CGEX using olive waste

Fig. 11

Effect of variation in the combustion temperature on LHV, HHV, and overall energy and exergy efficiencies using wood (Birch)

Fig. 12

Effect of variation in the combustion temperature on LHV, HHV, and overall energy and exergy efficiencies using olive waste

## Tables

Table 1 The descriptions of equipment labels used in the Aspen model
Table 2 The descriptions of stream labels used in the aspen model
Table 3 The chemical reactions taking place in the gasifier
Table 4 The chemical composition of Olive waste and wood (Birch) used in aspenplus modeling (Adopted from Ref. [23])
Table 5 The parameters used in aspenplus simulation (modified from Ref. [11])

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