ORIGINAL ARTICLE

Hydrogen-Rich Syngas Production by Plasma Gasification of Existing Biomasses in Cuba

MSc. Jorge Jadid Tamayo-Pacheco^{I  *}  , MSc. Leonardo Peña-Pupo^II  , Dr.C. Arelys Vázquez-Peña^III  , Dr.C. Ángel Luis Brito-Sauvanell^IV 

^IUniversidad de Oriente, Facultad de Ingeniería Eléctrica, Santiago de Cuba, Cuba.

^IIEmpresa de Hidroenergía UEB Santiago de Cuba, Cuba.

^IIIInstituto de Ciencia Animal, San José de las Lajas, Mayabeque, Cuba.

^IVUniversidad de Oriente, Centro de Estudios de Energía y Refrigeración Facultad de ingeniería Mecánica, Santiago de Cuba, Cuba.

ABSTRACT

The production of 2nd generation biofuels is a transcendental issue for sustainability due to its influence on reducing fossil fuel consumption. One of the most recognized techniques for the production of biofuels starts from syngas with an H₂/CO = 2 molar ratio. This gas can be obtained through the biomass gasification process, a complex process with several operational parameters. The purpose of this study was to perform the simulation of the plasma gasification process of three biomasses that are abundant agro-industrial or forest residues in Cuba. For this, the graphic method and the exploration of the operating regions were used applying a model with a thermochemical equilibrium approach. As a result, it was obtained that it is possible to achieve a production of syngas with values between 1.79-2.80, 1.68-2.37 and 2.09-2.81 NM³/kg from sugarcane bagasse, rice husk and wood sawdust, respectively, with the cold gas efficiencies, in that same order, 31-65%, 20-49%, and 43-53%. In addition, the sensitivity analysis was carried out to identify the influential parameters on performance indicators.

Key words: Simulation of plasma gasification; thermodynamic analysis; sensitivity analysis

INTRODUCTION

Second-generation biofuels are those obtained from lignocellulose agricultural, industrial forest or municipal residues, as well as non-food energy crops. These biofuels do not compete with food production and are considered a sustainable and environmentally friendly option for the replacement of fossil fuels. The production of energy from biomass at the local or national level contributes to energy sovereignty and security while positively influencing the development of rural areas (^{Sikarwar et al., 2017}).

For the synthesis of second-generation liquid biofuels, one of the methods developed is thermochemistry. Through this method, biomass is converted into a hydrogen-rich gas that is subsequently used as a raw material for the synthesis of liquid fuels (^{Sikarwar et al., 2017}).

The adequate H₂/CO molar ratio is a requirement according to the subsequent use to be made of syngas, for example, an H₂/CO molar ratio of approximately 1.0 is required for the production of aldehyde and alcohol, while it is required an H₂/CO ratio close to 2.0 for the synthesis of biofuels and methanol according to the Fischer-Tropsch method (^{Im-orb et al., 2016}).

The present study is focused on evaluating one of the thermochemical methods with the possibility of producing a gas rich in hydrogen: the gasification of biomass using thermal plasma with air and steam as gasifying agents. This method is considered by some authors as an attractive and ecological option for waste treatment (^{Favas et al., 2017}).

In plasma gasification, with the high temperatures reached, the organic portion of the biomass is decomposed into its constituent elements, leaving also a partially inorganic vitrified slag (^{Favas et al., 2017}). The advantages are the controllability of the process temperature, higher process speeds, lower reactor volume and, especially, an optimal composition of the gas produced where the amount of tars is insignificant. Also, inorganic materials are recovered for their use in (^{Hrabovsky et al., 2017}). However, it has some notable drawbacks, such as high electricity consumption, the need for resistant materials given the high operating temperature and high investment costs. (^{Favas, et al., 2017}; ^{Sikarwar, et al., 2017}). On the other hand, this process can be understood as a store of electrical energy since it is, in a certain way, stored in the gas produced (^{Hrabovsky et al., 2017}).

Although there are currently waste treatment plants, mainly for urban solid and dangerous waste, that operate with the plasma gasification method, it is a technology whose maturity is debatable (^{Li et al., 2016}). The introduction of this technology implies challenges that begin with the knowledge of it through studies and technical-economic evaluations, for which the use of simulations is necessary.

Numerous studies have addressed the issue of the production of hydrogen-rich gas from biomass gasification, both from a theoretical and an experimental point of view (^{Parthasarathy and Narayanan, 2014}). But most of these studies are aimed at thermo-conversion by other methods such as rapid pyrolysis followed by steam reforming of coal, supercritical water gasification, and steam gasification but do not include plasma gasification (^{Parthasarathy and Narayanan, 2014}).

Some of the more recent works on plasma gasification to obtain hydrogen describe experimental results on a laboratory or pilot plant scale (^{Diaz et al., 2015}; ^{Hlina et al., 2014}; ^{Hrabovsky, et al., 2017}; ^{Shie et al., 2014}; ^{Tamošiūnas et al., 2016}; ^{Yoon and Lee, 2012}) pilotos (^{Diaz et al., 2015}; ^{Hlina et al., 2014}; ^{Hrabovsky, et al., 2017}; ^{Shie et al., 2014}; ^{Tamošiūnas et al., 2016}; ^{Yoon and Lee, 2012}); others include simulation from models (^{Diaz, et al., 2015}; ^{Favas, et al., 2017}; ^{Hrabovsky, et al., 2017}; ^{Ismail et al., 2019}; ^{Tamošiūnas, et al., 2016}; ^{Tavares et al., 2019}). Some use only the composition of syngas as performance criteria and do not address energy efficiency issues such as ^{Favas et al. (2017)}; ^{Tavares et al. (2019)} or as in the case of ^{Shie, et al. (2014)}, which simply describe the results of other authors where the feasibility of such technology is confirmed. Other works also include energy efficiency as a performance indicator ^{Hrabovsky et al. (2017)}; ^{Ismail et al. (2019)}; ^{Yoon and Lee (2012)}. ^{Tamošiūnas et al. (2016)} consider the carbon conversion, the specific energy required for the amount of syngas produced and the energy efficiency of the process, but do not include the energy consumed to generate the added water vapor.

The objective of this work is to evaluate the results of the plasma gasification of three biomasses present in Cuba, having as operational parameters the steam-biomass ratio (SBR), the equivalence ratio (ER) and the energy ratio between the enthalpy of plasma and the calorific value of biomass (PER). To do this, performance issues such as the composition of syngas and energy issues such as the cold gas efficiency (CGE) and the specific energy consumed per kg of hydrogen produced, among others, are assumed as performance indicators. This analysis is more comprehensive compared with the previously cited works. The approach used is novel because the joint effect of the parameters in the selected operating regions is analyzed, which constitute process restrictions. The study uses the graphic method and the exploration of the operating regions by means of a model with a thermochemical equilibrium approach. Finally, a sensitivity analysis of the model allows establishing the most influential parameters on the H₂/CO ratio, the calorific value, the efficiency and the specific production of the syngas.

METHODS

To simulate the process, in this study, a thermochemical equilibrium model was used. This type of model is very popular because it is relatively simple and the results to be obtained are close to reality, mainly in gasifiers that operate at high temperatures and with sufficient residence time in which the operational state is close to theoretical equilibrium. This type of model has previously been used to describe the plasma gasification process (^{Diaz et al., 2015}; ^{Mountouris et al., 2006}).

The model inputs include: the elemental composition of the biomass, its humidity and ash quantity, the amount of air that reacts, the amount of added steam, the enthalpy contributed to the reaction by the thermal plasma and the carbon ratio unconverted. The final composition of the syngas is the main output of the model and constitutes a basic element to later calculate the energy performance criteria. The energy of the thermal plasma was taken into account in the energy balance as in ^{Mountouris et al. (2006)} and it is shown in Equation 1. $$

${∆H}_{fbiomasa}^{°}+w\left({∆H}_{f{H}_{2}O}^{°}+H_{\left(vap\right)}\right)+m∆{\mathrm{T}}_{air}\left({Cp}_{{mO}_2}+3.76{Cp}_{{mN}_2}\right)+s\left({∆H}_{f{H}_{2}O\left(vap\right)}^{°}+∆{\mathrm{T}}_{steam}{Cp}_{{mH}_{2}O}\right)+QPlasma(100-Losses)/100=x_{CO}{∆H}_{fCO}^{°}+x_{{CO}_2}{∆H}_{f{CO}_2}^{°}+x_{H_{2}O}{∆H}_{f{H}_{2}O}^{°}+x_{{CH}_4}{∆H}_{f{CH}_4}^{°}+∆T\left(x_{H_2}{Cp}_{{mH}_2}+x_{CO}{Cp}_{mCO}+x_{{CO}_2}{Cp}_{{mCO}_2}+x_{H_{2}O}{Cp}_{{mH}_{2}O}+x_{{CH}_4}{Cp}_{{mCH}_4}+(3.76m+bN){Cp}_{N_2}\right)+{ncC\bullet Cp}_{mC}$ (1)

$\Delta H_{fi}^{°}$	enthalpy of formation of substance i [kJ/kmol]
$w$	amount of water contained in the biomass [mol]
s	amount of water vapor added [mol]
m	amount of air involved in the reaction [mol]
$QPlasma$	enthalpy provided by the thermal plasm [kJ]
$x_i$	amount of substance i present in the products [mol]
$C{p}_{mi}$	average specific heat of the i [kJ/(kmol∙K)]
$\Delta T$	temperature difference between the gasification temperature and 298 K° [K°]
$ncC$	unconverted carbon fraction [mol]
$H_{\left(vap\right)}$	enthalpy of water vaporization [kJ/kmol]
$\Delta {\text{T}}_{air}$	air temperature minus 298 K
$\Delta {\text{T}}_{steam}$	water vapor temperature minus 298 K
$\Delta T$	gasification temperature minus 298K
$Losses$	energy losses as % de $QPlasma$

Other equations that are part of the model are the mass balance of carbon, hydrogen, oxygen and nitrogen as in ^{Zainal et al. (2001)}

$bC=x_{CO}+x_{{CO}_2}+x_{{CH}_4}+ncC$ (2)

$2w+2s+bH=2x_{H_2}+2x_{H_{2}O}+4x_{{CH}_4}$ (3)

$w+s+bO+2m=x_{CO}+2x_{{CO}_2}+x_{H_{2}O}$ (4)

$bN+3.76\bullet 2m=2x_{N_2}$ (5)

Where $bC$ , $bH$ , $bO$ y $bN$ are the carbon, hydrogen, oxygen and nitrogen atoms in the simplified form of the biomass molecule, respectively.

The equilibrium constants of the methane formation reaction $K_1$ and the gas displacement reaction $K_2$ were written in correspondence with (^{Zainal, et al., 2001}):

$K_1=\frac{x_{{CH}_4}}{{x_{H_2}}^2}$ (5)

$K_2=\frac{x_{H_2}\bullet x_{{CO}_2}}{x_{CO}{\bullet x}_{H_{2}O}}$ (6)

The relationships between the operational parameters and the model inputs are:

$m=ER\bullet a_t$ (7)

$s=SBR\bullet M_{biomH}/18$ (8)

$Qplasma=PER\bullet {LHV}_{biom}$ (9)

Being $a_t$ the theoretical amount of air for complete combustion of one mole of biomass, $M_{biomH}$ the molar mass of the wet biomass and $LH{V}_{biom}$ the lower heating value of the dry biomass.

The system of equations of the model was solved following an algorithm similar to that proposed in ^{Melgar et al. (2007)}, where the gasification temperature is searched iteratively such that the set of equations is solved (2) to (6) and the energy balance of Equation (1) is met.

For the calculation of the specific heats, empirical expressions taken from ^{Smith (1950)}; ^{Zainal et al. (2001)}

The process performance indicators were calculated as:

$H2/CO=x_{H_2}/x_{{CO}_2}$ (10)

$CGE=\frac{H_{gas}}{{PCI}_{biom}+\frac{Q_{plasma}}{{\eta }_{torch}}+s\bullet H_{steam}}\bullet 100$ (11)

${PCI}_g=0.108\bullet X_{H_2}+0.126\bullet X_{CO}+0.358\bullet X_{{CH}_4}[MJ/m^3]$ (12)

$Electriccons.perkgofbiom.=\frac{Q_{plasma}}{{\eta }_{torch}{\bullet M}_{biomH}\bullet 3600}\left[\frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{k}\mathrm{g}\mathrm{}\mathrm{d}\mathrm{e}\mathrm{}\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}.}\right]$ (13)

$Electriccons.perkgof{\mathrm{H}}_2=\frac{Q_{plasma}}{{\eta }_{torch}\bullet 2{\bullet x}_{H_2}\bullet 3600}\left[\frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{k}\mathrm{g}\mathrm{}\mathrm{d}\mathrm{e}\mathrm{}{\mathrm{H}}_2}\right]$ (14)

Where $H_{gas}$ is the energy of the syngas produced by gasifying one mole of biomass calculated as the amount of the substance multiplied for its lower calorific value, $H_{steam}$ is the molar enthalpy of the water vapor added in kJ/kmol, $Xi$ denotes in percent the composition of the gas i.

Three biomasses present in Cuba were selected for the study: sugarcane bagasse, rice husk and wood sawdust. The first two have an agroindustrial origin and the second one, a woody origin. Their characteristics are shown in Table 1. It is noteworthy that these properties change according to the variety and weather conditions, so it is recommended to determine them experimentally for subsequent works. In the case of wood sawdust, a composition generally accepted by other authors was assumed (^{Zainal et al., 2001}):

TABLE 1 Characteristics of the studied biomass 

	Elemental Composition (dry basis)				Moisture %	Ash (dry basis)	Reference
	C%	H%	O%	N%
Bagasse	47.5	5.9	40.7	0.29	20	5.6	(Mavukwana et al., 2013)
Rice husk	38.4	2.97	36.4	0.49	9.95	21.7	(Loha et al., 2011)
Sawdust	50	6	44	0	10, 0	0	(Zainal et al., 2001)

The study carried out consisted of selecting an operation region for two of the operational parameters (PER and SBR). In this region, 120 points were explored and in each one the ER was increased, starting from zero until obtaining a value such that the restriction that the gasification temperature is equal to 1200 ° C, at which the formation of tars, is negligible (^{Rutberg et al., 2011}). To analyze the results obtained, the graphic method was used by drawing contour lines of the values of interest. The region of operation is limited to the level curve where H₂/O=2, it will be called: restricted region of operation. The level curve corresponding to the minimum ER=0 outside was also drawn. On the restricted operation region, the extreme points and an intermediate point were studied, for each one, the performance indicators of gas quality and energy issues were calculated.

For the sensitivity study, the graphic method of tornado diagrams obtained for each of the model inputs was used, considering, for each input, a variation of ± 10% of its nominal value. Values higher than nominal were not taken into account for the carbon conversion and for the torch efficiency because they were considered maximums, and the thermal losses in the gasifier were considered non-negative.

RESULTS AND DISCUSSION

Figure 1 shows the level curves of the H₂/CO ratio, the LHV of the syngas and the production of syngas per kilogram of biomass gasified. The restricted operation region, where the extreme points and an intermediate one were marked, is highlighted.

Following the H₂ /CO=2 curve in the direction of the increase in SBR, it happens that the ER must increase to decrease the positive effect of SBR on H₂/CO, but this causes an increase in temperature and to counteract it, PER must decrease. But PER also affects the composition of gases, an operating point must be achieved such that the effects of the decrease in PER and the increase in ER guarantee that the restrictions are met. Consequently, the LHV of the syngas decreases, the specific production increases and the amount of hydrogen produced decreases. The latter is mainly due to the greater presence of oxygen that favors obtaining water in the products. As it can be seen, there is a relationship among the three operational parameters in the restricted operation region, so it is not trivial to determine the joint effect of their variations.

Figure 1 Process performance in the operation area. 

Points A for bagasse and sawdust are close to plasma gasification with steam in the absence of air (ER = 0). For rice husk, an expansion of the area of operation in the direction of the decrease in SBR is still possible (See Figure 1).

The restricted operating region of bagasse is displaced towards lower SBR values compared to that of the other biomasses. The reason for this is that the hydrogen content in this wet biomass is higher than in the others, so the process requires less hydrogen from the steam. The operating points A of rice husk and sawdust are close. However, point B of sawdust is at a higher value of PER, since the latter biomass requires more external heat.

Table 2 summarizes the performance indicators related to the hydrogen production potential for the three biomasses at three points in the restricted operation region. Where it can be observed that the maximum hydrogen production per kg of biomass was obtained for the wood sawdust at point A, where ER is closest to zero; while the minimum was for rice husk at point B. In this indicator, wood sawdust outperforms bagasse and rice husk. This is explained by the composition of rice husk, which has the lowest percentage of carbon and hydrogen, in addition to the highest percentage of ash of the three biomasses.

The highest production of syngas was obtained at points B of bagasse and sawdust (see Table 2). For bagasse and rice husk there are operating points in which the gas PCI is less than 4 MJ / Nm3, which limits its application for energy purposes. The syngas with the highest hydrogen composition were obtained at points A of bagasse and sawdust and the lowest at point B of rice husk.

TABLE 2 Performance indicators of syngas production 

	Cane Bagasse			Rice husk			Wood sawdust
	Pt. A	Pt. I	Pt. B	Pt. A	Pt. I	Pt. B	Pt. A	Pt. I	Pt. B
SBR	1.07	1.39	1.70	1.45	1.75	2.0	1.45	1.63	2.0
PER	0.45	0.27	0.10	0.44	0.28	0.15	0.44	0.34	0.24
ER	0.05	0.34	0.61	0.20	0.45	0.70	0.05	0.22	0.40
mH2 /mbiom (g/kg)	83	58	34	54	37	20	97	80	61
Prod. (Nm^3/kg)	1.79	2.31	2.80	1.68	2.02	2.37	2.09	2.45	2.81
LHVg (MJ/Nm^3)	9.01	4.83	2.35	6.14	3.50	1.63	8.94	6.24	4.26
H%	52	28.10	13.76	35.84	20.55	9.64	51.94	36.60	25.11

Table 3 summarizes the performance indicators related to energy efficiency for the three biomasses at three points in the restricted operation region. The highest cold gas efficiency was obtained for bagasse at point A, and the lowest for rice husk at point B. For rice husk, the CGE was less than 50% in the three points, so it would be necessary to extend the region of operation in the sense of decreasing SBR to operate the process with a higher CGE value.

Interestingly, at points A, the CGE is higher, with those having the highest PER values in the three biomasses. The explanation for this fact is that, at points A, the ER is minimal and the amount of nitrogen in the syngas is notably less. Furthermore, at these points, the amount of H₂ and CO are greater, so the calorific value of syngas is several times higher. At points B, the CGE is diminished because the high ER values favor the water vapor content more than the H2 content in the syngas. The highest electricity consumption of plasma per kg of biomass corresponds to sawdust at point A and the lowest to point B of bagasse. In the three points the sawdust required a higher electrical consumption per kg of biomass.

The electric consumption per kg of H₂ was higher in rice husk in the three points, while in the lowest of all, it was point B of bagasse. This is an information that can be used in dimensioning plasma torches. In general, at all points, the electrical consumption per kg of H₂ was lower than the average electrical consumption in the hydrolysis process (55 kWh/kg of H₂). This demonstrates how advantageous it could be to produce hydrogen by biomass gasification compared to removing it from water by hydrolysis.

TABLE 3 Performance indicators of the energy efficiency of the process 

	Cane bagasse			Rice husk			Wood sawdust
	Pt. A	Pt. I	Pt. B	Pt. A	Pt. I	Pt. B	Pt. A	Pt. I	Pt. B
CGE	65	49	31	49	36	20	63	54	43
Electric cons. (kWh/kg of bio.)	1.95	1.17	0.43	1.48	0.99	0.49	2.23	1.72	1.21
Electric cons. (kWh/kg of prod. H 2 )	24.40	20.18	12.59	27.53	26.52	24.17	23.00	21.50	19.7

In this study, the possibility of taking advantage of the sensible heat of the syngas to produce part of the steam added to the process was not considered; but it is something that must be taken into account in subsequent investigations. Figure 2 shows how superior the sensible heat of the syngas is compared to the latent and sensible heat of the steam involved in the process. The idea of recovering this heat has been raised by some authors ^{Hrabovsky et al. (2017)} and in ^{ZHU (2015)}, that this can increase efficiency by up to 5 percentage points.

Figure 2 Sensitive heat of syngas and steam at intermediate points when gasifying 1 kg of biomass. 

The sensitivity analysis was performed at the points previously defined as "I" with similar results for the three biomasses. Figure 3 shows the local sensitivity analysis for the point I of bagasse, in addition to PER, ER and SBR. Other variables were incorporated into the study such as biomass humidity, steam temperature, unconverted carbon, thermal losses in the gasifier and torch efficiency.

Figure 3 shows that the LHV of the syngas is strongly affected by the ER and it does it in the opposite way, that is, a greater ER implies a lesser LHV and vice versa. Furthermore, this indicator is significantly affected by the non-conversion of carbon, since it causes less presence of carbon monoxide and methane in the syngas.

The H₂/CO ratio is strongly influenced by SBR directly, while ER and PER do it inversely and to a lesser extent. On this indicator the effect of steam temperature is inverse, but with small relevance, while energy losses have a direct influence. The biomass moisture favors this indicator too.

For CGE the determining factor is the non-conversion of carbon, since the more unconverted carbon, the lower the efficiency and, in the same sense, the ER and PER influence and the effect of ER is greater than that of PER. Torch efficiency has a direct effect on EGF.

Figure 3 Local sensitivity analysis for point I. Sugarcane bagasse. 

Syngas production mainly depends on carbon conversion and to a lesser extent on biomass moisture and ER. The other factors do not affect it appreciably.

CONCLUSIONS

The method of exploring the regions of operation made possible to study the interactions between the operational parameters with the performance criteria of plasma gasification. In the restricted operation region for the three biomasses, the points where SBR is minimum (ER is minimum and PER maximum) the gas has higher quality, using hydrogen production as a criterion, and the efficiency of cold gas is higher. However, at these points, the electrical consumption of the plasma is higher.

Of the three biomasses studied, wood sawdust is the most convenient for the process of obtaining syngas rich in hydrogen, since it is possible to produce more hydrogen (97 g / kg of biomass). But, it is also where greater electrical consumption of plasma torches is necessary (2.23 kWh/kg of biomass). In this sense, rice husk presents the worst results with a maximum specific hydrogen production of 54 g/kg of biomass with 27.5 kWh/kg of the produced hydrogen.

As a final conclusion, this study verified that plasma gasification with mixtures of air and steam as a gasifying agent can be used for the production of a gas rich in hydrogen, with specific productions in the ranges 1.79-2.80, 1.68-2.37 and 2.09- 2.81 NM³/kg from sugarcane bagasse, rice husk and wood sawdust, respectively, and this with a lower electricity consumption per kilogram of hydrogen than that of water hydrolysis.

Although plasma gasification technology applied to agro-industrial waste is not sufficiently mature globally, it must be seen as a possible path for the production of second-generation biofuels.

ACKNOWLEDGMENT

The authors thank the Cuban energy transformation Integration of renewable intermittent sources in the power system (IRIS) project and the VLIR-IUC-UO Program, for their help to finance this research.

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6The mention of trademarks of specific equipment, instruments or materials is for identification purposes, there being no promotional commitment in relation to them, neither by the authors nor by the publisher.

Received: December 12, 2019; Accepted: September 25, 2020

^*Author for correspondence: Jorge Jadid Tamayo-Pacheco, e-mail: [e-mail]

Jorge Jadid Tamayo Pacheco, Profesor, Universidad de Oriente, Facultad de Ingeniería Eléctrica, Santiago de Cuba, Cuba, e-mail: [e-mail]

Leonardo Peña Pupo, Inv., Empresa de Hidroenergía UEB Santiago de Cuba, Cuba, e-mail: [e-mail]

Arelys Vázquez Peña, Arelys Vázquez-Peña, Investigadora, Instituto de Ciencia Animal, San José de las Lajas, Mayabeque, Cuba, e-mail: [e-mail]

Ángel Luis Brito Sauvanell, Profesor, Universidad de Oriente, Centro de Estudios de Energía y Refrigeración Facultad de ingeniería Mecánica, Santiago de Cuba, Cuba, e-mail: [e-mail]

The authors of this work declare no conflict of interests.