Upscaling Effects on Char Conversion in Dual Fluidized Bed Gasification

Subscriber access provided by - Access paid by the | UCSB Libraries

Biofuels and Biomass

Upscaling Effects on Char Conversion in Dual Fluidized Bed Gasification Louise Lundberg, David Pallares, and Henrik Thunman Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b00088 • Publication Date (Web): 10 Apr 2018 Downloaded from http://pubs.acs.org on April 11, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Upscaling Effects on Char Conversion in Dual Fluidized Bed Gasification Louise Lundberg*, David Pallarès, Henrik Thunman Chalmers University of Technology, Dept. SEE–Energy Technology

Abstract Dual fluidized bed gasification (DFBG) is an emerging technology that can be employed as a first step in the transformation of lignocellulosic materials into transportation fuels such as substitute natural gas, dimethyl ether, methanol, and Fischer-Tropsch diesel. The present work aims at: i) identifying challenges that arise in the upscaling of DFBG plants; ii) determining whether the increased fuel residence time that results from the upscaling is sufficient for process optimisation; and iii) evaluating the impact of measures to mechanically control the fuel residence time. The investigations use a semi-empirical 1-dimensional model, which is validated with industrial-scale measurements. The scope includes both DFBG units delivering gas as the main product and those in which the product gas is a by-product in a heat and power plant. Moreover, both new designs and retrofit cases of existing CFB combustion plants (i.e., adding a gasifier to the return leg) are considered. Modelling results show that although there is an initial increase in the fuel residence time as the size of the gasifier increases, further upscaling eventually leads to a decrease in the degree of char gasification due to: i) a decrease in the fuel residence time, as there is a transition in lateral fuel mixing from the dispersion-dominant regime to the convectiondominant regime; and ii) a decrease in the char gasification rate due to an increased bed material velocity, which increases the probability that pyrolysis occurs on the bed surface (leading to a less reactive char as the heat transfer is lower there compared to inside the dense bed). For DFBG units of around 100 MW, proper combinations of operational conditions (e.g., the solids circulation, the steam-fuel ratio, and the temperature of the circulating solids),

1 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

result in an optimised process when heat and power is the main product, with gas as a byproduct. However, when gas is the sole targeted product, it is likely that baffles are also necessary to achieve sufficient fuel conversion for process optimisation.

1. INTRODUCTION In order to decrease CO2 emissions from the transportation sector, lignocellulosic materials can be transformed into gaseous or liquid transportation fuels, such as methanol, dimethyl ether, substitute natural gas (SNG), and Fischer-Tropsch Diesel.1,2 The first step in this process is to transform the feedstock into a raw gas, which is subsequently cleaned and upgraded into the desired transportation fuel. Fluidized bed (FB) gasifiers are a suitable technology for this first step. There are two major FB gasification techniques: i) direct gasification, in which the heat required to sustain the endothermic gasification reactions is provided by burning part of the fuel within the gasifier;2 and ii) indirect gasification (also called dual fluidized bed gasification, DFBG), in which the necessary heat is provided by circulating bed material between a combustor and the gasifier,1 see Figure 1. In direct gasification, the gasifier is fluidized either by air—which results in dilution of the product gas with N2—or with a mixture of H2O and pure O2, which demands O2 production and thus has a significant inherent energy penalty.2 In contrast, in DFBG, the increased capital cost related to the need for two FB reactors is compensated by the fact that the gasifier can be fluidized with pure H2O or CO2, which results in a raw product gas with a much higher heating value (typically around 14–18 MJ/Nm3, compared to 4–7 MJ/Nm3 for direct gasification on a dry gas basis)3.1 Furthermore, complete fuel burnout can be difficult to attain for direct gasification, whereas this is more easily achieved for DFBG. An advantage with direct gasification is that pressurisation of the system is easier, whereas this is impractical for DFBG as it consists of


Page 2 of 33

Page 3 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

two reactors. While direct gasification is a mature technology with several commercial-scale units in operation worldwide (see e.g., 4), the upscaling of DFBG is in progress (e.g., the GoBiGas plant in Göteborg, Sweden),5 see Table 1. The aim of the present work is to identify the challenges that arise in the upscaling of DFBG plants, to determine whether the increased fuel residence time that results from the upscaling is sufficient for process optimisation, and to evaluate the impact of measures to mechanically control the fuel residence time. The investigations use a semi-empirical 1dimensional model, which is validated with industrial-scale measurements. The scope includes both DFBG units delivering gas as the main product and those in which the product gas is a by-product in a heat and power plant. Moreover, both new designs and retrofit cases of existing CFB combustion plants (i.e., adding a gasifier to the return leg) are considered. The gasification chamber is assumed to be at bubbling conditions, and its cross section is rectangular. The analysis is limited to the char conversion in the gasification chamber of a DFBG system, which, as discussed in Section 2, is a crucial parameter for the design and optimisation of the DFBG technology.6

2. CONTROL OF LARGE-SCALE DFBG SYSTEMS The combustor in a DFBG system converts the char remaining after passing through the gasification chamber, and thus the thermal power in the combustor is given by eq (1). ܲୡ୭୫ୠ = ݉ሶ୊ ܻୡ୦ୟ୰ ൫1 − ܺୡ୦ୟ୰,୥ ൯‫ܸܪܮ‬ୡ୦ୟ୰ =

ܻୡ୦ୟ୰ ൫1 − ܺୡ୦ୟ୰,୥ ൯‫ܸܪܮ‬ୡ୦ୟ୰ ܲ୲୭୲ ‫ܸܪܮ‬୊

(1)

A DFBG plant can be designed and/or operated in two distinctly different ways, depending on whether the main product is: i.

gas, which typically is to be further upgraded (into e.g., a transportation fuel such as SNG, or a broad platform compound such as methanol). In this case, the optimum overall efficiency of the system is achieved when there is a thermal balance between 3 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 4 of 33

the combustor [Pcomb in eq (1)] and the internal heat demand of the DFBG unit (i.e., the additional fuel feed to the combustor in Figure 1 is zero). This occurs when the degree of char conversion in the gasification chamber, Xchar,g in eq (1), is at its optimal ୭୮୲

୭୮୲

value, ܺୡ୦ୟ୰,୥. Char gasification degrees below ܺୡ୦ୟ୰,୥ create a need for additional cooling of the system, which implies a high penalty in the plant efficiency, whereas higher values result in a need to burn part of the raw gas (with a much lower plant efficiency penalty). ୭୮୲

ܺୡ୦ୟ୰,୥ depends on factors such as the composition of the feedstock (moisture content, volatile yield, and char yield), the desired end-product, and temperatures and magnitudes of the gas flows fed into the unit. For example, a high moisture content will result in a high heat demand for drying, which will result in a lower Xchar,gopt. Likewise, a higher volatile yield (and consequently a lower char yield) will require more heat for pyrolysis (and less for char gasification), and as the char yield is lower ୭୮୲

the fraction of the char required for combustion (1– ܺୡ୦ୟ୰,୥) will increase so that ୭୮୲

୭୮୲

ܺୡ୦ୟ୰,୥ decreases. ܺୡ୦ୟ୰,୥ typically lies within the interval 10–50% (see Larsson et al.)6.

ii.

heat and power (by means of a steam cycle), with gas production as a by-product. The gas can either be upgraded to e.g., methanol or SNG, or used to increase the power production of the unit through a gas turbine. In this case, the gas produced comes from pyrolysis of the fuel, and the degree of char conversion within the gasification chamber should be minimised to avoid an increased heat demand in the gasifier (i.e., Xchar,g ≈ 0). In this mode, additional fuel can be supplied to the combustor to fulfil the heat and power demands (Figure 1).


Page 5 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Furthermore, designing a DFBG plant so that operation can be switched between the two above-cited modes (a so-called poly-generation unit) would increase the flexibility of the DFBG technology, which is forecasted as a critical feature for thermochemical fuel conversion in an energy system with an increased share of non-dispatchable heat and power. Out of the different combinations regarding the types of fluidized beds used in DFBG, that in which the combustor is a circulating fluidized bed (CFB), and the gasifier is a bubbling fluidized bed (BFB) has been found to be the most effective,7 and coincides with the design of the operational state-of-the-art biomass DFBG units given in Table 1. Efficient operation of DFBG plants in either of the two modes described above requires the ability to control and optimise the degree of char conversion in the gasification chamber, Xchar,g. Likewise, successful upscaling of DFBG to commercial scales requires a good understanding for how the fuel conversion, and in particular Xchar,g, is influenced by scale. Figure 2 depicts the underlying mechanisms behind the resulting level of char conversion within the gasification chamber, which ultimately depends on the fuel residence time8,9 and the char gasification rate, both of which are affected by the fuel mixing. The fuel residence time (τF, see Section 3.1.) increases with reactor size and decreases with fuel lateral mixing (which is notably enhanced if the fuel particles are located on the bed surface)10. Two ways to control τF are by: i) adjusting the operational parameters (e.g., the fluidization velocity and the solids cross-flow, u0 and ṁBM in Figure 1, respectively);11 and ii) using baffles (which allows a more compact design of the gasifier, yielding lower capital and operational costs), see Section 3.1.12 The char gasification rate (see Section 3.2.) is strongly affected by the temperature within the gasifier and the steam concentration in the emulsion phase (Figure 2).13 Available tools for controlling the temperature are the solids cross-flow,14 and the temperatures of the


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

incoming bed material and steam. The steam concentration in the emulsion phase can be influenced by the steam-fuel-ratio (SFR) and the choice of bed material. Control of the flow and temperature of the solids entering the gasifier (ṁBM and TBM,in in Figure 1) is thus crucial for process optimisation. The solids input temperature can be controlled by letting the solids pass through a heat exchanger before entering the gasifier. An increase in ṁBM can be achieved by increasing the solids circulation flux in the boiler. A further control tool, which does not require varying the conditions in the combustion reactor, can be provided by a convenient design of the particle sealing system. A specific example of this is the Chalmers DFBG system (used for model validation, see Section 4.2.1), see Figure 3. Originally, the Chalmers system consisted of a 12 MW CFB boiler whose return leg was (and still is) equipped with an external heat exchanger (called particle cooler, see 3 in Figure 3), used to control the temperature of the circulating solids and to which a share of the circulating solids can be deviated when needed. This was later retrofitted into a DFBG unit by adding a 2–4-MW BFB gasifier to the return leg, to which a share of the circulating solids can also be directed (through the fluidization velocity in the connecting loop seal, see 4 in Figure 3). Thus, the circulating solids are divided into three streams flowing: i) through the external heat exchanger; ii) through the gasifier; and iii) directly back to the combustor. In large-scale BFB units the bed height is limited to a few decimetres since the bubbles grow in size with bed height, which results in a significantly decreased mass transfer of gas between the bubble and emulsion phases.15 This in turn leads to a reduction in the steam-fuel contact, which limits char gasification.16 Thus, for commercial scales, cross-sectional upscaling (i.e., increasing the cross-sectional area of the gasifier without increasing the bed height) must be applied, not only to keep constant levels of the fluidization velocity, but also to limit the bubble size. 6 ACS Paragon Plus Environment

Page 6 of 33

Page 7 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Note that DFBG systems offer the possibility to use high pressure process steam to fluidize the bed. Through the use of a high pressure drop over the gas distributor the bubble size becomes smaller than in classical low-pressure gas distributors.17 As described above, decreasing the bubble size results in an improved mass transfer between the gas and emulsion phases and thus an increase in the steam-fuel contact. Cross-sectional upscaling yields a larger cross-section compared to upscaling in all three dimensions. Some consequences of this are higher capital costs, and the fact that the circulation of bed material between the BFB gasifier with its large cross-sectional area and the comparatively small CFB combustor could result in a challenge regarding the spatial design. Furthermore, while laboratory-scale BFB units often have a circular cross-section, for larger units it is more cost-effective to build rectangular geometries.

3. THEORY 3.1. Fuel Residence Time. The average residence time of the fuel within the gasification chamber is estimated according to eq (2).8 This equation, which assumes that the velocity field of bed material within the gasifier is uniform, combines the timescales of the dispersive fuel flow, τd, [eq (3)], and the convective fuel flow induced by the cross-flow of bed material, τc [eq (4)]. ߬୊ = ሺ1/߬ୡ + 1/߬ୢ ሻିଵ

(2)

߬ୢ = ‫ܮ‬ଶ /ሺ2‫ܦ‬୊ ሻ

(3)

߬ୡ = ߬୆୑ /ߠ୊ = ݉୆୑ /ሺ݉ሶ୆୑ ∙ ߠ୊ ሻ

(4)

The time scale of fuel dispersion, τd [eq (3)], depends on the reactor length, L, and the fuel dispersion coefficient, DF. Thus, for the conditions assumed in this work (constant length/width-ratio (L/W) and constant area load, Qcr (W/m2), see Section 4.2.2), τd increases proportionally with the scale of the gasifier.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

The time scale of fuel convection, τc [eq (4)], depends on the time scale for the mixing of bed material within the gasifier, τBM, and the cross-flow impact factor, θF (see Section 4.1.2.). For constant values of the ṁBM/ṁF-ratio (the solids cross-flow normalised with the fuel feeding rate to the gasification chamber), L/W, and Qcr, τBM is independent of scale. However, since θF increases with the bed material velocity (see Table 2), which in turn increases with scale, τc decreases with an increase in gasifier size, until θF = 1 is reached [i.e., when τF = τBM ≠ f(scale)]. Thus, as the gasifier size increases, fuel convection becomes more dominant compared to fuel dispersion, i.e., the solids circulation assumes a more dominant role on the fuel residence time than the fluidization velocity or the dense bed height. The present work uses a 1-dimensional model to model char conversion in the bottom bed of a BFB gasifier with a rectangular cross-section. For this type of gasifier geometry, the 1-dimensional approach works rather well for industrial-scale units (see Figure 5 for modelled and experimentally measured char gasification degrees within the Chalmers gasifier) as the velocity field can be assumed to be fairly uniform along the gasifier. Furthermore, as long as the L/W-ratio is kept constant during upscaling (which is the case in the present work) the description of the fuel conversion for larger units will be as reasonable as for the validation case. As mentioned in Section 2, the fuel residence time can be increased by adding baffles to the gasification chamber. This effect has been experimentally investigated in the Chalmers gasifier,12 and it resulted in increased degrees of char gasification (8–15 percentage points higher compared to when no baffles were employed). The baffles, which were partially submerged into the bed, were thin, rectangular steel plates with a height of 0.5 m and with a width equal to that of the Chalmers gasifier. For commercial use, in order to avoid wear, the baffles should be made of a ceramic material or a highly alloyed steel and the gas velocities close to the baffles should be minimised. 8 ACS Paragon Plus Environment

Page 8 of 33

Page 9 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

3.2. Char Gasification Rate. As seen in Figure 2, in addition to temperature and steam concentration, the char gasification rate is also influenced by the fuel axial mixing (i.e., whether the fresh fuel and char are converted on the bed surface or inside the dense bed) through its effect on the heat and mass transfer between the bed and the fuel particles,16 which in turn affect the char structure and the resulting char reactivity.13,16 The char gasification rate is thus, to some extent, influenced by the fluidization velocity and the solids cross-flow, since these parameters influence the fuel axial mixing.9,18 Lundberg et al.16 found that the gasification rate of wood pellets decreased by 50% when pyrolysis occurred at the bed surface (low heat transfer yielding a less reactive char) and char gasification inside the dense bed (low mass transfer yielding a slower transport of the gasifying agent to the char particle).9,18 The present work takes into account the effect of operational conditions on the char gasification rate by means of their influence on the axial distribution of fuel. This is done by determining the fraction of fuel particles that undergo pyrolysis on the bed surface and char gasification inside the dense bed, FBS/IB, according to the method described in Lundberg et al.,9 and by setting their char gasification rate 50% lower than for all other fuel particles. FBS/IB increases with bed material velocity,9 which increases with scale. Thus, the char gasification rate will decrease with scale until FBS/IB reaches unity. Furthermore, the char gasification rate is affected by a number of other parameters, such as char reactivity,13 fuel size,16,19 volatile inhibition,20 catalytic bed material effects,21 and ash effects.22

4. MODELLING 4.1. 1D Model of Gasifier. The present work uses semi-empirical modelling, in which transport equations are used to solve mass and heat balances, whereas velocity fields are given by semi-empirical correlations. This is the most widely used approach to model solid fuel


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 33

conversion in large-scale fluidized beds (see e.g., 23-26 for models of fluidized bed combustion and 27-30 for gasification), and it was chosen as it offers reliability and enough level of detail to a relatively low computational cost.3 In the steady-state semi-empirical 1D model used here (see Lundberg et al.14 for a previous version), the dense bottom bed of the gasification chamber is discretised in the direction of the solids cross-flow. The model input/output scheme is given in Figure 4a, whereas Figure 4b shows the mass and energy flows considered by the model, as well as the direction of discretisation. The model does not include unburnt char entering the gasifier with the solids (circulated char in Figure 1). The origin of such char is either recirculated char from the fuel fed to the gasifier or unburnt char from an additional fuel feed to the combustor. The total amount of circulated char in the Chamers DFBG system has been estimated to be rather low (0–0.125 kgchar,circ/kgfed char,gasifier),6 where most of the circulated char likely originates from the additional fuel fed to the boiler. The model solves the mass and heat balances given by eqs (5)–(9). Values or empirical correlations used to estimate parameters in eqs (5)–(9) (e.g., dispersion coefficients), as well as additional parameters used in the 1D-model, are given in Table 2. Mass balance for gas species i in bubble phase: 0 = ߜୠ ‫ܭ‬ୠୣ ൫ߩୋ,ୣ ܻୣ,୧ − ߩୋ,ୠ ܻୠ,୧ ൯ + ܵୠ,୧

(5)

Mass balance for gas species i in emulsion phase: 0 = ߜୠ ‫ܭ‬ୠୣ ൫ߩୋ,ୠ ܻୠ,୧ − ߩୋ,ୣ ܻୣ,୧ ൯ +

݀ ܻ݀ୣ,୧ ൬‫ߩ ܦ‬ ൰ + ܵୣ,୧ ݀‫ ݔ‬ୋ ୋ,ୣ ݀‫ݔ‬

(6)

Mass balance of fuel component k of class j: 0=−

݀ߩ୩,୨ ݀ ݀ ൫ߠ୊ ‫ݑ‬୆୑ ߩ୩,୨ ൯ + ቆ‫ܦ‬୊ ቇ + ܵ୩,୨ ݀‫ݔ‬ ݀‫ݔ‬ ݀‫ݔ‬

(7)

Potential flow model for the velocity field of bulk solids: 0=

݀ ݀ߔ୆୑ ൬‫ܦ‬୆୑ ൰ + ܵ୆୑ ݀‫ݔ‬ ݀‫ݔ‬

(8a)


Page 11 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

‫ݑ‬୆୑ =

‫ܦ‬୆୑ ݀ߔ୆୑ ൬ ൰ ߩ୆୑ ݀‫ݔ‬

(8b)

Heat balance: 0 = −‫ܥ‬୮,୆୑

+

݀ ݀ ݀ ݀ߩ୩ ଶହԨ ଶହԨ ሺ‫ܶ ߩ ݑ‬ሻ − ෍ ൫ߠ୊ ‫ݑ‬୆୑ ߩ୩ ℎ୤,୩ ൯ + ෍ ൬‫ܦ‬୊ ℎ୤,୩ ൰ ݀‫ ݔ‬୆୑ ୆୑ ݀‫ݔ‬ ݀‫ݔ‬ ݀‫ݔ‬ ௞

௞

݀ ܻ݀ୣ,୧ ଶହԨ ݀ ݀ܶ ൭෍ ൭‫ܦ‬ୋ ߩୋ,ୣ ቀℎ୤,୧ + ‫ܥ‬୮,୧ ሺܶ − 25Ԩሻቁ൱൱ + ൭ሺ݇ + ݇ ᇱ ሻ ൱ + ܵ୉ ݀‫ݔ‬ ݀‫ݔ‬ ݀‫ݔ‬ ݀‫ݔ‬

(9)

࢏

The velocity field of the bulk solids induced by the solids cross-flow is calculated assuming it to follow a potential flow function, ΦBM, according to eqs (8a–b).11 4.1.1. Mass Balances for Gas Species. The gas flow is described by the two-phase model approach proposed by Toomey and Johnstone,31 which divides the gas into two phases: i) the emulsion phase (containing gas needed for minimum fluidization and all solids); and ii) the bubble phase (containing all excess gas fed to the bed, i.e., that corresponding to a volumetric flux of u0–umf). The two-phase model was chosen over more detailed approaches (e.g., the inclusion of a cloud phase) due to that the gas concentration fields are not resolved in the axial direction and that literature lacks bubble-emulsion interphase coefficients in largescale units, so more details would add complexity to the model without increasing the reliability of the results. Thus, for each gas species, two mass balances are formulated that correspond to the bubble phase [eq (5)] and the emulsion phase [eq (6)]. The gas species considered are CO, CO2, H2, H2O, CH4, and tars (represented by C6H6O). The first term on the right-hand-side (RHS) of eqs (5) and (6) describes mass transfer between the bubble phase and the emulsion phase, which is governed by the bubble-emulsion interchange coefficient, Kbe. The second term in eq (6) describes lateral gas transport within the emulsion phase, governed by the lateral gas dispersion coefficient, DG. The final term in eqs (5) and (6) are the source terms, which include reactions (the water-gas-shift reaction) and transport into and out of the gasifier, i.e., the gas entering the reactor and that leaving at the bed surface.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

It is assumed that drying and pyrolysis occur on the bed surface, and thus that the gases released by these do not enter the bottom bed region. This is in line with empirical observations,18 and is to some extent due to the lifting force of the endogenous bubbles formed around the fuel particles during pyrolysis,32 which has been confirmed for industrialscale beds in the Chalmers gasifier using a hot-temperature camera probe.18 4.1.2. Mass Balances for Fuel Species. The reactive fuel components (moisture, volatiles and char), k, are each divided into a number of classes, j, based on the degree of conversion (see Lundberg et al.),33 all for which a mass balance [eq (7)] is solved. Eq (7) is also used to calculate the concentration field of ash along the gasifier, using a single nonreactive class. Eq (7) includes convective and dispersive mass transport, as well as a source term that includes reactions and transport into and out of the gasifier. The convective transport is governed by the cross-flow impact factor, θF, which describes the extent to which the fuel particles follow the velocity field of the bed material induced by the solids cross-flow. The insertion of baffles (the “baffle-equipped gasifier”, see Section 4.2.2) is handled by setting the dispersion coefficient, DF, to a low value (DF,low = 10–6 m2/s) and the cross-flow impact factor, θF, to zero at the given mesh grid points corresponding to the baffle locations. As seen in Figure 4a, a submodel based on a particle model (described in Lunderg et al.),33 is run for a given fuel prior to the model simulations to generate an interpolation table with values of the apparent conversion rate of conversion class j in fuel component k (Rk,j) for a range of steam concentrations and/or temperatures. The effects of char shrinkage and char fragmentation are not accounted for by the model. In a previous experimental investigation by the authors,16 where wood pellets underwent steam gasification in a laboratory-scale fluidized bed, no significant char fragmentation or char shrinkage was observed for a char gasification degree of 62%. Thus, for


Page 12 of 33

Page 13 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

the incomplete char gasification of wood pellets modelled in the present work, it is reasonable to neglect these phenomena. Moreover, the model does not explicitly account for volatile inhibition (nth order kinetics are assumed). As mentioned in Section 4.1.1., in line with empirical observations, pyrolysis is assumed to occur on the bed surface such that the pyrolysis gases do not enter the bottom bed region where char gasification occurs. In this case, the only species causing volatile inhibition are CO and H2 produced during char gasification. Furthermore, in the determination of the kinetic data for char gasification used in the present work using the afore-mentioned laboratory-scale fluidized bed gasifier (see 34), the inhibitory effects of H2 and CO are included indirectly, as these species are present in the emulsion phase during char gasification in the experiments. 4.1.3. Heat Balance. A single heat balance [eq (9)] is solved for both gas and solids (including fuel). The temperature difference between the fuel particles and the gas/bed material caused by the endothermic nature of the gasification reactions is accounted for when estimating the rates of drying, pyrolysis, and char gasification with the afore-mentioned particle-model based sub model (see Figure 4a), which solves the transient temperature field within a fuel particle. Furthermore, in eq (9) it is assumed that the reacting fuel components remain at the fuel inlet temperature until they are converted, whereas ash and bed material are heated to the bed temperature. The first and second terms on the RHS of eq (9) describe convective heat transfer by the bed material and the fuel, respectively. The third and fourth terms represent the heat transported by fuel and gas dispersion, respectively, whereas the fifth term designates heat transfer due to temperature gradients, i.e., conduction, k, and that related to the mixing of bulk solids, k’ (see Table 2). The final (source) term represents the energy flows into and out of the gasifier, i.e., feeding and outlet of fuel, bulk solids, and gas. 13 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 33

4.2. Methodology. First, the model is validated against a series of industrial-scale cases (Section 4.2.1.). Thereafter, model simulations are used to investigate the upscaling of DBFG systems (Section 4.2.2.). 4.2.1. Model Validation. Israelsson et al.35 performed experiments in the Chalmers 2–4MW indirect gasifier using wood pellets as fuel and silica sand as bed material (see Table 6), varying the input solids temperature (840°C–876°C) and the SFR (0.44–0.64). The degree of char conversion in the gasification chamber can be estimated for six runs from the total carbon in the raw gas, which was measured after letting the raw gas pass through a hightemperature combustion reactor36 that converted the gas to a mix of exclusively CO, CO2, H2, and H2O: ୫ୣୟୱ ܺୡ୦ୟ୰ =1−

‫ܥ‬୊,ୢୟ୤ − ‫ܥ‬ୋ ܻୡ୦ୟ୰ ∙ ܻେ,ୡ୦ୟ୰

(10)

The uncertainty in the char yield (19% ± 1%),16 as well as in the amount of carbon in the char (96% ± 4%)37 yields a certain confidence interval in the values obtained by eq (10). As mentioned in Section 4.1., since the amount of circulated char from the combustor into the gasifier has been estimated to be rather low (0–0.125 kgchar,circ/kgfed char,gasifier),6 it is not included in eq (10). 4.2.2. Upscaling Simulations. Eight different DFBG units are considered in Sections 5.2 and 5.3, depending on the main target product (gas as sole product or heat and power, with gas as a by-product), whether it is a new design or a retrofit of an existing plant, and on the scale of the gasifier (small: 1–10 MW; large: ≥ 100 MW), see Table 3. Table 4 gives geometrical data for the gasification chamber of DFBG units of the different scales investigated in the present work. Two gasifier designs are considered: i) a base-case (BC) gasifier with no baffles; and ii) a baffle-equipped gasifier with two baffles at x/L = 0.2 and 0.8. In Section 5.2., the base-case


Page 15 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

gasifier is compared to two cases using the baffle-equipped gasifier (Table 5). The following means for controlling the char conversion degree within the gasifier are also considered in the present work: adjusting the operational conditions (the solids circulation rate, TBM,in, TH2O,in, and the SFR; and using a catalytic bed material (discussion only). The model input parameters used for the upscaling simulations in the present work are given in Table 6.

5. RESULTS AND DISCUSSION 5.1. Validation. Figure 5 shows experimental (six measurements in total, described in Section 4.2.1.)35 and modelled values for the degree of char conversion in the Chalmers gasifier, as a function of the input temperature of bed material and the SFR. As seen, the modelled results give a fairly satisfactory fit with the experimental measurements. However, the significant uncertainties in the experimental data (see Section 4.2.1.) should be noted. As seen in Figure 5, both experimental and modelled values of Xchar,g increase with the solids input temperature and decrease with the SFR. The fluidization velocity, u0, and consequently the fuel lateral dispersion (DF, see Table 2), increase with the SFR. Therefore, the observed decrease of Xchar,g with an increase of the SFR is caused by the decrease in fuel residence time as the fuel lateral dispersion increases. 5.2. Upscaling –Target: Gas as Sole Product. When gas is aimed as sole product, the ୭୮୲

lowest acceptable value of Xchar,g is ܺୡ୦ୟ୰,୥ in eq (1), see Section 2. In Figure 6, the modelled degree of char conversion in the base-case gasifier is plotted as a function of the ṁBM/ṁF-ratio for Ptot = 1, 10, 100, and 420 MW for two values of the SFR. Figure 6 also shows the resulting Xchar,g for the two baffle cases described in Table 5. As the fuel residence time and the temperature have opposite trends with the solids crossflow (see Figure 7 for the 100 MW base-case gasifier and SFR = 0.4), the char conversion curves for any unit scale present a peak when plotted as a function of the ṁBM/ṁF15 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ratio. The extra peaks observed in two cases (420 MW, SFR = 0.3 and 100 MW, SFR = 0.4) are due to the sudden variation in the derivative of τF(ṁBM/ṁF) that can be observed in Figure 7, which makes the temperature effect on Xchar,g more dominant. As the scale increases, τF and thus Xchar,g initially increase. However, as discussed in Section 3.1., as the scale increases further there is a transition from the dispersion-dominant regime to the convection-dominant regime, which results in a decrease in τF and Xchar,g. As seen in Figure 6, the influence of scale on the char gasification degree decreases as the SFR is increased from 0.3 to 0.4, due to that convection becomes more dominant as the SFR increases. Furthermore, as discussed in Section 3.2 and for operational and geometrical conditions relevant in the present work, the char gasification rate decreases with scale, which contributes to the observed decrease in the degree of char gasification with scale. As mentioned in Section 2, optimal char conversion degrees lie in the range of 10%– 50%.6 As seen in Figure 6, although upscaling initially leads to a natural increase in τF (and Xchar,g), it is likely that Xchar,g is not sufficiently high to achieve process optimisation, i.e., ୭୮୲

ܺୡ୦ୟ୰,୥. However, by introducing baffles and adjusting the operational conditions, process optimisation is deemed possible. Another way to further increase Xchar,g, outside of the scope of this work, is the use of a catalytic bed material, which can enhance the char gasification rate.21 5.3. Upscaling –Target: Heat and Power Production with Gas as By-Product. In this production mode, char conversion should be as low as possible, whereas the extent of pyrolysis should be as close as possible to 100%. Figure 8 shows, for base case gasifiers with a fuel input (Ptot) of 1 MW and 100 MW, the degrees of char gasification and pyrolysis (Xchar,g and Xpyr) in the gasifier as a function of the ṁBM/ṁF-ratio. Two different inlet solids temperatures are considered: 700°C—below which char gasification is considered negligible—and 900°C—a typical temperature level for CFB combustors. 16 ACS Paragon Plus Environment

Page 16 of 33

Page 17 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

As seen in Figure 8a, for the small-scale base case gasifier τF becomes too short to achieve complete pyrolysis (i.e, Xpyr < 1). Increasing TBM,in from 700°C to 900°C results in a higher level of pyrolysis, but also an increase in char gasification. For larger units, however, complete pyrolysis (Xpyr = 1) is easily achieved at low solids cross-flows, even at low temperatures, due to the long τF (Figure 8b). At high temperatures, a significant amount of char is also converted. Thus, for both small and large scales, TBM,in and the solids circulation should be limited so that the gasifier temperature is kept low in order to avoid char gasification. However, as seen in Figure 8a, for the smaller gasifier sizes, this may lead to incomplete pyrolysis, so the residence time needs to be increased, e.g., by means of baffles, as shown in Section 5.2.12 The same challenges and solutions as those stated above also apply for the retrofit of an existing CFB combustor into a DFBG unit keeping heat and power as the main production target. If it is possible to extract a controllable amount of heat from the circulating solids prior to their entrance into the gasifier, e.g., with the use of an external particle cooler (as described in Section 2) the combustor load can be easily varied without necessarily affecting the heat conveyed to the gasifier. Furthermore, the control of the temperature of the circulating solids yields a flexible size of the gasifier to be added, especially if baffles are used to control the fuel residence time. 5.4. Upscaling –Target: Poly-Generation. DFBG systems designed for heat and power production as main product are in general difficult to switch into operation with gas production as the main target. This is due to that the relatively small gasifier existing in order to reach the fuel residence time necessary for complete pyrolysis will not allow significant levels of char gasification. As for DFBG units designed for gas production, their operation can be switched to target heat and power by decreasing the temperature within the gasifier in order to avoid char 17 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

gasification. This can be achieved by bypassing a suitable part of the solids circulation flow (exemplified with the Chalmers DFBG unit in Section 2). Thus, poly-generation units, i.e., those with a flexible output with controllable shares of heat, power and gas, should follow the design guideline for units devoted to gas production, namely a large gasifier (enabling enough fuel residence time for char gasification when needed in the gas production mode) and the possibility to control the flow and/or temperature of the solids flow entering the gasifier (e.g., by means of a by-pass system or an external heat exchanger prior to the gasification chamber).

6. CONCLUSIONS Semi-empirical modelling has been shown able to describe the heat and mass transfer in the gasification chamber of an industrial-scale indirect gasification system. Use of this model to study process optimisation upon upscaling shows that different challenges arise in the design and operation of DFBG systems, depending on whether the DFBG unit is a new design or a retrofit of an existing CFB combustor, and on the main production target (solely gas, or heat and power with gas as by-product). Upscaling initially results in a natural increase in the fuel residence time, as the size of the gasifier increases. However, the modelling conducted in the present work shows that after a certain size, further increasing the scale leads to a decrease in the char gasification degree for two reasons: i) the fuel residence time decreases as there is a transition in fuel lateral mixing from the dispersion-dominant regime to the convection-dominant regime; and ii) for operational and geometrical conditions relevant for the present work, increasing the scale results in a decrease in the char gasification rate. This is due to that the bed material velocity increases with scale, resulting in an increased probability that pyrolysis occurs on the bed


Page 18 of 33

Page 19 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

surface (which in turn leads to a less reactive char since the heat transfer is lower there compared to inside the dense bed). For DFBG units of around 100 MW, proper combinations of operational conditions (e.g., the solids circulation, the steam-fuel ratio, and the temperature of the circulating solids), result in an optimised process when heat and power is the main product, with gas as a byproduct. However, when gas is the sole targeted product, it is likely that baffles are also necessary to achieve sufficient fuel conversion for process optimisation. The same type of solutions can be applied for retrofits of existing CFB boilers to DFBG units as those for newly designed DFBG units. Poly-generation units with the flexibility to switch their main output between heat and power and gas production should be designed with a relatively large gasifier (yielding high enough fuel residence times for char gasification to take place) and a by-passable external heat exchanger (allowing the decrease of the temperature in the gasifier required in the heat and power production mode).

ACKNOWLEDGMENTS The authors express their gratitude for the financial support provided by: the Swedish Gasification Centre (SFC) within the framework of the Centre for Indirect Gasification of Biomass (CIGB); and Energiforsk, the Swedish Energy Agency, and Göteborg Energi within the framework of the project Char Conversion in Fluidized Bed Indirect Gasification (39972– 1).

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]. Tel: +46 (0)31 772 14 38 Notes


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

The authors declare no competing financial interest.


Page 20 of 33

Page 21 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

REFERENCES (1) Hofbauer, H. Scale Up of Fluidized Bed Gasifiers from Laboratory Scale to Commercial Plants: Steam Gasification of Solid Biomass in a Dual Fluidized Bed System. FBC19, Vienna, Austria, 2006. (2) Neubauer, Y. 6 - Biomass gasification. In: Biomass Combustion Science, Technology and Engineering. 1st ed. Woodhead Publishing, 2013; pp 106-129. (3) Gómez-Barea, A.; Leckner, B. Modeling of biomass gasification in fluidized bed. Prog. Energ. Combust. 2010, 36, 444-509. (4) Plants -licensed SGT projects. http://www.synthesisenergy.com/plants: Synthesis Energy Systems; 2017. (5) Gunnarsson, I. The GoBiGas Project; Technical Report. Göteborg, Sweden: Göteborg Energi; 2011. (6) Larsson, A.; Seemann, M.; Neves, D.; Thunman, H. Evaluation of performance of industrial-scale dual fluidized bed gasifiers using the Chalmers 2-4-MWth gasifier. Energy Fuels. 2013, 27, 6665-6680. (7) Xu, G.; Murakami, T.; Suda, T.; Matsuzawa, Y.; Tani, H. The superior technical choice for dual fluidized bed gasification. Ind. Eng. Chem. Res. 2006, 45, 2281-2286. (8) Sette, E.; Pallarès, D.; Johnsson, F. The influence of operating conditions and fuel-feed location on fuel residence time in an indirect gasifier. 11th International Conference on Fluidized Bed Technology, CFB 2014, Chemical Industry Press: Beijing, 2014. pp 809-814. (9) Lundberg, L.; Soria-Verdugo, A.; Pallarès, D.; Johansson, R.; Thunman, H. The role of fuel mixing on char conversion in a fluidized bed. Powder Technol. 2017, 316, 677-686. (10) Chirone, R.; Miccio, F.; Scala, F. On the relevance of axial and transversal fuel segregation during the FB combustion of a biomass. Energy Fuels. 2004, 18, 1108-1117. 21 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(11) Sette, E.; Pallarès, D.; Johnsson, F. Influence of bulk solids cross-flow on lateral mixing of fuel in dual fluidized beds. Fuel Process. Technol. 2015, 140, 245-251. (12) Larsson, A. Fuel conversion in a dual fluidized bed gasifier -experimental quantification and impact on performance. Doctoral Thesis, Chalmers University of Technology, Göteborg, Sweden, 2014. (13) Di Blasi, C. Combustion and gasification rates of lignocellulosic chars. Prog. Energ. Combust. 2009, 35, 121-140. (14) Lundberg, L.; Pallarès, D.; Johansson, R.; Thunman, H. A 1-dimensional model of indirect biomass gasification in a dual fluidised bed system. 11th International Conference on Fluidized Bed Technology, CFB 2014, Chemical Industry Press: Beijing, 2014. pp 607-612. (15) Kunii, D., Levenspiel, O. Fluidization Engineering; Butterworth-Heinemann: Newton, 1991. (16) Lundberg, L.; Tchoffor, P. A.; Pallarès, D.; Johansson, R.; Thunman, H.; Davidsson, K. Influence of surrounding conditions and fuel size on the gasification rate of biomass char in a fluidized bed. Fuel Process. Technol. 2016, 144, 323-333. (17) Svensson, A.; Johnsson, F.; Leckner, B. Fluidization regimes in non-slugging fluidized beds: the influence of pressure drop across the air distributor. Powder Technol. 1996, 86, 299312. (18) Sette, E.; Berdugo Vilches, T.; Pallarès, D.; Johnsson, F. Measuring fuel mixing under industrial fluidized-bed conditions - A camera-probe based fuel tracking system. Appl. Energ. 2016, 163, 304-312. (19) Nilsson, S.; Gómez-Barea, A.; Cano, D. F. Gasification reactivity of char from dried sewage sludge in a fluidized bed. Fuel. 2012, 92, 346-353.


Page 22 of 33

Page 23 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

(20) Nilsson, S.; Gómez-Barea, A.; Fuentes-Cano, D.; Campoy, M. Gasification kinetics of char from olive tree pruning in fluidized bed. Fuel. 2014, 125, 192-199. (21) Arjmand, M.; Leion, H.; Lyngfelt, A.; Mattisson, T. Use of manganese ore in chemicallooping combustion (CLC)-Effect on steam gasification. Int. J. Greenh. Gas Con. 2012, 8, 5660. (22) Perander, M.; DeMartini, N.; Brink, A.; Kramb, J.; Karlström, O.; Hemming, J.; Moilanen, A.; Konttinen, J.; Hupa, M. Catalytic effect of Ca and K on CO2 gasification of spruce wood char. Fuel. 2015, 150, 464-472. (23) Pallarès, D. Fluidized bed combustion -modelling and mixing. Doctoral Thesis, Chalmers University of Technology, Göteborg, Sweden, 2008. (24) Hannes, J. P. Mathematical Modelling of Circulating Fluidized Bed Combustion. Doctoral Thesis, Technical University of Delft, Delft, Netherlands, 1996. (25) Ratschow, L. Three-Dimensional Simulation of Temperature Distributions in LargeScale Circulating Fluidized Bed Combustors. Doctoral Thesis, Technical University of Hamburg-Harburg, Hamburg, Germany, 2009. (26) Myöhänen, K. Modelling of combustion and sorbent reactions in three-dimensional flow environment of a circulating fluidized bed furnace. Doctoral Thesis, Lappeenranta University of Technology, Lappeenranta, Finland, 2011. (27) Nikoo, M. B.; Mahinpey, N. Simulation of biomass gasification in fluidized bed reactor using ASPEN PLUS. Biomass Bioenerg. 2008, 32, 1245-1254. (28) Jiang, H.; Morey, R. V. A numerical model of a fluidized bed biomass gasifier. Biomass Bioenerg. 1992, 3, 431-447. (29) Radmanesh, R.; Cnaouki, J.; Guy, C. Biomass gasification in a bubbling fluidized bed reactor: Experiments and modeling. AIChE J. 2006, 52, 4258-4272. 23 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(30) Petersen, I.; Werther, J. Three-dimensional modeling of a circulating fluidized bed gasifier for sewage sludge. Chem. Eng. Sci. 2005, 60, 4469-4484. (31) Toomey, R. D., Johnstone, H.F. Gaseous fluidization of solid particles. Chem. Eng. Prog. 1952, 48, 220-225. (32) Bruni, G.; Solimene, R.; Marzocchella, A.; Salatino, P.; Yates, J. G.; Lettieri, P.; Fiorentino, M. Self-segregation of high-volatile fuel particles during devolatilization in a fluidized bed reactor. Powder Technol. 2002, 128, 11-21. (33) Lundberg, L.; Johansson, R.; Pallarès, D.; Thunman, H. A conversion-class model for describing fuel conversion in large-scale fluidized bed units. Fuel. 2017, 197, 42-50. (34) Lundberg, L., Tchoffor, P.A., Johansson, R., Pallarès, D. Determination of Kinetic Parameters for the Gasification of Biomass Char Using a Bubbling Fluidised Bed Reactor. 22nd International Conference on Fluidized Bed Conversion, Turku, Finland, 2015. (35) Israelsson, M.; Berdugo Vilches, T.; Thunman, H. Conversion of Condensable Hydrocarbons in a Dual Fluidized Bed Biomass Gasifier. Energy Fuels. 2015, 29, 6465-6475. (36) Israelsson, M.; Larsson, A.; Thunman, H. Online measurement of elemental yields, oxygen transport, condensable compounds, and heating values in gasification systems. Energy Fuels. 2014, 28, 5892-5901. (37) Neves, D.; Thunman, H.; Matos, A.; Tarelho, L.; Gómez-Barea, A. Characterization and prediction of biomass pyrolysis products. Prog. Energ. Combust. 2011, 37, 611-630. (38) Biomass CHP Plant Senden. http://www.repotec.at/index.php/96.html: Repotec. (39) Wilk, V.; Hofbauer, H. Analysis of optimization potential in commercial biomass gasification plants using process simulation. Fuel Process. Technol. 2016, 141, 138-147. (40) Hofbauer, H.; Aichernig, C. Fluidized bed gasification based on steam: the Güssing example. VDI Berichte. 2005, 1891, 197-211. 24 ACS Paragon Plus Environment

Page 24 of 33

Page 25 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

(41) Hrbek, J. Status report on thermal biomass gasification in countries participating in IEA Bioenergy Task 33. International Energy Agency; 2016. (42) Ondrey, G. Startup for a new gasification process. Chem. Eng.-New York. 2015, 122, 10. (43) Sette, E.; Pallarès, D.; Johnsson, F. Experimental quantification of lateral mixing of fuels in fluid-dynamically down-scaled bubbling fluidized beds. Appl. Energ. 2014, 136, 671-681. (44) Oka, S. Fluidized Bed Combustion; Marcek Dekker Inc: New York, 2004. (45) Darton, R. C.; LaNauze, R. D.; Davidson, J. F.; Harrison, D. Bubble growth due to coalescence in fluidised beds. Trans. Inst. Chem. Eng. 1977, 55, 274-280. (46) Wen, C. Y.; Yu, Y. H. A generalized method for predicting the minimum fluidization velocity. AIChE J. 1966, 12, 610-612. (47) Cui, H.; Mostoufi, N.; Chaouki, J. Characterization of dynamic gas–solid distribution in fluidized beds. Chem. Eng. J. 2000, 79, 133-143. (48) Leva, M. Fluidization; McGraw-Hill: New York, 1959.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figures

Figure 1. The principle of DFBG.

Figure 2. Factors affecting the degree of char conversion in the gasification chamber of a DFBG unit.


Page 26 of 33

Page 27 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Figure 3. Part of the Chalmers DFBG unit, showing the particle distributor, gasifier, particle cooler, and loop seals.

Figure 4. a) Model structure; and b) boundary energy and mass flows considered by the model, as well as the direction of discretisation given by the grey lines.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 5. Char conversion in the Chalmers gasifier as a function of: a) inlet solids temperature; and b) SFR.

Figure 6. Degree of char conversion as a function of the ṁBM/ṁF-ratio for different scales and gasifier designs when gas is the sole targeted product for: a) SFR = 0.3 and b) SFR = 0.4.


Page 28 of 33

Page 29 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Figure 7. The average temperature within the gasifier versus the fuel residence time for the 100 MW base-case gasifer and SFR = 0.4.

Figure 8. Pyrolysis and char conversion degrees as a function of the ṁBM/ṁF-ratio when gas is a by-product in heat and power production for base-case gasifiers of: a) 1 MW; and b) 100 MW.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 33

TABLES Table 1. Operational biomass DFBG units.

Unit Gobigas5 Senden38 Oberwart39 Güssing40 Burgeis41 Chalmers6 IHI Tigar42,b a b

Plant type New design New design New design New design New design Retrofit New design

Thermal input/product 32 MWth/20 MWSNG 14 MWth/5 MWel 8.5 MWth/2.8 MWel 8 MWth/2 MWel 2 MWth/0.5 MWel 2–4 MWth/a 6–9 MWth/1800 Nm3 syngas/day

Start-up 2013 2011 2008 2002 2012 2007 2015

The raw product gas is torched in the CFB boiler. Commercialisation planned for 2018.

Table 2. Equations or values for the empirical parameters used in the model.

Model parameter DBM (m2/s) DF (m2/s) DG (m2/s) θF (–) Kbe (s-1) db0 (m) db (m) db,av (m) Remf (m/s) εmf (–)

δb (–) εe (–) k’ (W/m/K)

Value/equation 7.3·10–3·u0 + 1.3·10–2 3.3·10–2·u0 – 4.0·10–4 10–4 θF ∈ [0,1] 4.7·u0 – 0.52, uBM = 0.009 m/s 5.7·u0 – 0.63 uBM = 0.012 m/s 4.5· (umf/db,av)+5.85· (DG0.5g0.25/db,av1.25) 1.63[(u0–umf)·A0/g0.5]0.4 0.54(u0–umf)0.4·(H+4·A00.5)0.8g–0.2 db0[(H = 0)+db(H = Hbed)]/2 (33.72 + 0.0408Ar)1/2 – 33.7 Ar = 1.75/(εmf3φBM)·Remf2 +150(1– εmf)/(εmf3φBM2) ·Remf 0.534–0.534·exp(–(u0–umf)/0.413) 0.62–0.059·exp(–(u0–umf)/0.429) DBM·ρBM·Cp,BM +DF·ρash·Cp,ash

Table 3. Types of DFBG units considered in the present work.

Main target Gas Gas Gas Gas Heat and power Heat and power Heat and power Heat and power

New design/retrofit New design New design Retrofit Retrofit New design New design Retrofit Retrofit

Scale Small Large Small Large Small Large Small Large


Ref Sette et al.43 Sette et al.18 Oka44 Sette et al.11 Sette et al.11 Oka44 Darton et al.45 Darton et al.45 Wen and Yu46 Kunii and Levenspiel15

Cui et al.47 Cui et al.47 –

Page 31 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Table 4. Size specifications for the gasification chambers of DFBG units of different scales investigated in the present work.

Ptot L (m) W (m) Across (m2)

1 MW 1.1 0.5 0.5

10 MW 3.4 1.5 5

100 MW 10.6 4.7 50

420 MW 21.7 9.7 210

Table 5. Baffle cases investigated in Section 5.2.

Input parameter TH2O,in (°C) SFR (–) ṁBM/ṁF (–)

Baffle case 1 (baf1) 200 0.3 or 0.4 10

Baffle case 2 (baf2) 800 1.0 10

Table 6. Input parameters in the 1D model used for the upscaling simulations.

Input parameter Ptot Qcr = ṁFLHVF/Across L/W ∆Pbed TBM,in TH2O,in TF,in SFR ṁBM/ṁF (–) Fuel Type Ymoist (as received) Yash (daf) Ychar (daf) YC,char (ash-free) YC,F (daf) YH,F (daf) YO,F (daf) LHVF (as received) LHVchar (ash-free) dF ρF Char reactivity Bed material Type ρBM dBM φBM

Value(s) 1–420a MW 2 MW/m2 2.25 6 kPa 700°C–900°C 200–800°C 25°C 0.3b–1 2–25 Wood pellets 9% 0.5% 19% 100% 51% 6% 43% 16.9 MJ/kg 30.5 MJ/kg 8 mm 1105 kg/m3 From Lundberg et al.34 Silica sand 2700 kg/m3 292 µm 0.86 (from Leva48) 31 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 32 of 33

Ptot = 420 MW corresponds to the retrofit of a 100 MW combustor into a DFBG unit, given by eq (1) with ܺୡ୦ୟ୰,୥= 30% and the remaining ୭୮୲

a

parameters taken from Table 6. b

In order to avoid the risk of defluidization, the SFR is set so that u0/umf ≥ 3.7 (achieved in the Chalmers gasifier).35 As u0/umf is temperature-

dependent, this corresponds to a variation of the minimum SFR applicable for the different modelled cases (here 0.3–0.5).

ABBREVIATIONS Roman letters A0 Across Ar BFB C CFB CH2O Cp D d DFBG FB FP/CG g H hf25°C k k' L LHV Kbe m ṁ ∆Pbed Pcomb Ptot Qcr R Re RHS S SFR SNG Y Yash Ychar Ymoist Yi T u u0 X x W

Greek letters

bed cross-section/number of holes (m2) cross-section of gasifier (m2) Archimedes number (–) bubbling fluidized bed mass of carbon per kg daf fuel (kg/kgF,daf) circulating fluidized bed steam concentration (mol/moltot) heat capacity (J/(kg·K)) dispersion coefficient (m2/s) diameter (m) dual fluidized bed gasification fluidized bed fraction of fuel particles gravitational acceleration (m/s2) bed height (m) heat of formation at 25°C (J/kg) thermal conductivity (W/(m·K)) dispersion heat transfer coefficient (W/(m·K)) gasifier length (m) lower heating value (MJ/kgF) bubble-emulsion interphase coefficient (s–1) mass (kg) mass flow (kg/s) pressure drop over bed (Pa) combustor fuel demand (MW) total fuel input to DFBG unit (MW) gasifier area load (W/m2) gasification rate (s–1) Reynolds number (–) right-hand-side source term (depends on equation) steam-fuel-ratio (kg/kgF) substitute natural gas mass fraction (kg/kg) ash content (kg/kgF,daf) char yield (kg/kgF,daf) moisture content (kg/kgF) mass fraction of gas species i (kg/kg) temperature (ºC) velocity (m/s) fluidization velocity (m/s) degree of conversion (–) space coordinate of discretisation (m) gasifier width (m)

δ ε θ ρ τ Φ φ

volume fraction (–) voidage (–) cross-flow impact factor (–) concentration, density (kg/m3) residence time (s) potential flow function (kg/m3) sphericity (–)

Indices 0 av b BM BS c C CG d daf e E F g G H H2O i IB in j k meas mf O opt P vol

initial average bubble bed material bed surface convective carbon char gasification dispersive dry ash-free emulsion energy fuel gasifier gas hydrogen steam gas species inside dense bed inlet conversion class fuel component experimentally measured minimum fluidization oxygen optimal pyrolysis volatiles


Page 33 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels


Upscaling Effects on Char Conversion in Dual Fluidized Bed Gasification

Recommend Documents